Work on AI at scale
Our platforms have delivered 40M+ assessments and 5M+ evaluations — you’ll be building AI/ML systems that run at real, high-stakes scale, not a demo.
Careers
Build the AI that universities and enterprises run their assessments on.
Splashgain hires across engineering, AI/ML, product and customer success to keep building Eklavvya and DocuExprt for 500+ customers in 17+ countries.
Why join
Real AI, running at real scale
Join Splashgain and be part of our mission to transform software product development. We’re a fast-growing team serving clients across India and abroad, looking for passionate people who want to innovate, collaborate, and make an impact.
Work with cutting-edge technology, share ideas freely, and grow with a team that values creativity and learning. If you’re ready to take your career to the next level, we can’t wait to meet you.
Own outcomes, not tickets
A lean, AI-first team means engineers, product and customer success work close to the customer — from a university COE to an enterprise HR team — and see their work ship and get used.
Patent-grade engineering
Splashgain holds an India and Worldwide PCT patent for its Onscreen Marking System — an example of the kind of original technical work the team is expected to keep producing.
Global customer base
With customers across 17+ countries, you’ll work on multi-language, multi-region product problems from day one.
Why work with us
How the job actually works
Remote-First Culture
Work from anywhere with flexible hours and global collaboration.
Learning & Development
Continuous learning opportunities and skill development programs.
Work-Life Balance
Flexible schedules and time off to maintain healthy work-life balance.
Selection process
What happens after you write to us
- 1
Phone / Virtual Video Interview
Initial screening call to discuss your background and interest.
- 2
First Interview
Technical or role-specific interview with team members.
- 3
Technical Test
Practical assessment to evaluate your technical skills.
- 4
Offer
Final decision and offer discussion.
Open roles
18 openings, full-time and internship
Full-time roles across engineering, AI/ML, marketing, pre-sales and finance, plus internships that run three to six months. Open a role to see what it covers, then email us your CV with the job title in the subject line.
Senior Accounts Executive
FinanceIn-office / Hybrid2-3 yearsFull-Time
Our growing company is looking for an experienced and resourceful Senior Accounts Executive. The candidate will be responsible and accountable for performing end-to-end execution of bookkeeping, accounting, GST, TDS, and MIS. The position will be responsible for ensuring accuracy of the monthly accounting and reporting.
Senior Accounts Executive
FinanceIn-office / Hybrid2-3 yearsFull-Time
Our growing company is looking for an experienced and resourceful Senior Accounts Executive. The candidate will be responsible and accountable for performing end-to-end execution of bookkeeping, accounting, GST, TDS, and MIS. The position will be responsible for ensuring accuracy of the monthly accounting and reporting.
What you’ll do
- Prepare day-to-day accounting (AP, AR, JE, etc.) including taxation
- Responsible for monthly Invoicing and AR management for the company
- Handle Accounts Payable to ensure correct accruals and payment within credit period
- Maintain reporting accuracy for monthly financial statements (P&L, Balance Sheet, and Cash Flow Statement)
- Coordinate with respective stakeholders like consultants, CA, CS for GST, Income Tax, and ROC/MCA compliances
- Perform Bank Reconciliation and Interest Calculations for OD/CC accounts on regular basis
- Maintain accurate Inventory/Stock record on monthly basis
- Update work-related trackers on regular basis
- Leverage ChatGPT and AI tools for financial analysis, reporting automation, and process optimization
- Prepare MIS reports and financial dashboards using MS Excel and AI-powered analytics
- Ensure compliance with tax regulations, GST filing, and statutory requirements
- Manage cash flow and working capital for operational efficiency
Required skills & technologies
- Tally: Expert-level proficiency in Tally ERP 9 / Tally Prime for accounting and GST compliance (Must have)
- Taxation: Strong knowledge of GST, TDS, Income Tax, and applicable Indian tax laws
- MS Excel: Advanced Excel skills including Pivot Tables, VLOOKUP, Macros, and financial modeling
- MIS Reporting: Ability to prepare comprehensive MIS reports, financial dashboards, and variance analysis
- Bank Reconciliation: Expertise in bank reconciliation statements and interest calculations for OD/CC accounts
- Zoho Books: Experience with Zoho Books or similar cloud-based accounting software (preferred)
- Financial Reporting: Preparation of P&L, Balance Sheet, Cash Flow Statements, and financial analysis
- Cash Flow Management: Working capital management, cash flow forecasting, and liquidity analysis
- ChatGPT: Use of ChatGPT and AI tools for financial report generation, data analysis, and process automation
- GST Compliance: Filing GSTR-1, GSTR-3B, GST reconciliation, and GST portal operations
- QuickBooks: Experience with QuickBooks is an added advantage
- Accounts Payable & Receivable: Strong expertise in AP/AR management, credit control, and vendor management
Requirements & qualifications
- Commerce Graduate (B.Com, M.Com) with 2-3 years of experience in a CA firm or in an Indian company
- Hands-on experience in Tally is a must. Experience in QuickBooks, Zoho Books will be an added advantage
- Excellent verbal and written communication skills
- Ability to coordinate with various stakeholders for implementing required activities
- Persuasive and goal-oriented with a proactive approach
- Team handling experience is an added advantage
- Excellent analytical and time-management skills
- Strong attention to detail and accuracy in financial reporting
- Ability to work independently and meet deadlines in a fast-paced environment
- Familiarity with ROC/MCA filings and statutory compliance procedures
AI Marketing Manager
MarketingHybrid / In-office4-7 yearsFull-Time
Lead marketing initiatives for our AI-powered assessment and proctoring platform. Leverage cutting-edge AI tools and data-driven strategies to drive growth, brand awareness, and customer acquisition in the EdTech and HR Tech sectors.
AI Marketing Manager
MarketingHybrid / In-office4-7 yearsFull-Time
Lead marketing initiatives for our AI-powered assessment and proctoring platform. Leverage cutting-edge AI tools and data-driven strategies to drive growth, brand awareness, and customer acquisition in the EdTech and HR Tech sectors.
What you’ll do
- Develop and execute AI-powered marketing strategies using ChatGPT, Google Gemini for content generation and campaign optimization
- Create data-driven marketing campaigns using AI analytics tools and marketing automation platforms
- Utilize ChatGPT and AI writing tools for creating compelling content, ad copy, email campaigns, and social media posts
- Implement marketing automation using HubSpot, Marketo, or Salesforce Marketing Cloud integrated with AI tools
- Analyze marketing performance using Google Analytics 4, SQL queries, and AI-powered BI tools (Tableau, Power BI)
- Leverage AI for SEO optimization, keyword research using tools like SEMrush, Ahrefs with AI capabilities
- Design personalized customer journeys using AI-powered recommendation engines and behavioral analytics
- Manage digital advertising campaigns on Google Ads, LinkedIn, Facebook with AI bid optimization
- Create thought leadership content around AI, machine learning, and proctoring technology
- Collaborate with product teams to position AI features and benefits effectively
Requirements & qualifications
- Expertise in AI-powered marketing tools: ChatGPT, Google Gemini, Jasper AI, Copy.ai
- Marketing Automation: HubSpot, Marketo, Salesforce Marketing Cloud, Pardot
- Analytics: Google Analytics 4, Mixpanel, Amplitude, Hotjar
- Data Analysis: SQL, Python (pandas), Excel, Google BigQuery
- SEO/SEM: SEMrush, Ahrefs, Moz, Google Search Console, Google Ads
- CRM: Salesforce, HubSpot CRM, with AI integration capabilities
- Content Management: WordPress, Webflow, Contentful
- Social Media: LinkedIn Ads, Facebook Ads Manager, Twitter Analytics
- Email Marketing: Mailchimp, SendGrid, Brevo with AI personalization
- AI Tools: ChatGPT for content creation, Claude for analysis, Midjourney/DALL-E for visuals
- Understanding of B2B SaaS marketing and EdTech/HR Tech industry
- Experience with ABM (Account-Based Marketing) platforms and strategies
Digital Marketing Specialist (AI-Focused)
MarketingHybrid / In-office2-5 yearsFull-Time
Drive digital marketing campaigns for our AI-powered platforms using modern marketing technologies and AI tools. Focus on performance marketing, content creation, and data-driven optimization.
Digital Marketing Specialist (AI-Focused)
MarketingHybrid / In-office2-5 yearsFull-Time
Drive digital marketing campaigns for our AI-powered platforms using modern marketing technologies and AI tools. Focus on performance marketing, content creation, and data-driven optimization.
What you’ll do
- Create high-quality content using ChatGPT, Google Gemini for blogs, whitepapers, case studies, and marketing materials
- Manage paid advertising campaigns with AI optimization on Google Ads, LinkedIn, Facebook
- Execute SEO strategies using AI-powered keyword research and content optimization tools
- Design email marketing campaigns with AI personalization and segmentation
- Analyze campaign performance using Google Analytics, SQL queries, and data visualization tools
- Create engaging social media content and manage community engagement using AI scheduling tools
- Implement A/B testing frameworks using AI-powered experimentation platforms
- Develop landing pages and conversion funnels optimized with AI insights
- Collaborate with design teams using AI tools like Canva AI, Figma with AI plugins
- Track KPIs and create performance dashboards using Tableau, Power BI, or Google Data Studio
Requirements & qualifications
- AI Content Creation: ChatGPT, Google Gemini, Claude, Jasper, Copy.ai
- SEO Tools: SEMrush, Ahrefs, Moz, Surfer SEO (AI-powered), Pardot
- Advertising Platforms: Google Ads, Facebook Ads, LinkedIn Ads, Twitter Ads
- Analytics: Google Analytics 4, Google Tag Manager, Hotjar, Mixpanel
- Email Marketing: Mailchimp, HubSpot, SendGrid, ActiveCampaign
- Social Media Management: Hootsuite, Buffer, Sprout Social with AI scheduling
- Design Tools: Canva, Adobe Creative Suite, Figma
- Data Analysis: SQL, Excel, Google Sheets, basic Python for data manipulation
- Marketing Automation: HubSpot, Marketo, or similar platforms
- CMS: WordPress, Webflow, HubSpot CMS
- AI Image Generation: Midjourney, DALL-E, Stable Diffusion for visual content
Content Marketing Specialist (AI & Tech)
MarketingHybrid / In-office3-5 yearsFull-Time
Create compelling technical content that showcases our AI-powered assessment and proctoring solutions. Use advanced AI tools to produce high-quality blogs, technical documentation, case studies, and thought leadership pieces.
Content Marketing Specialist (AI & Tech)
MarketingHybrid / In-office3-5 yearsFull-Time
Create compelling technical content that showcases our AI-powered assessment and proctoring solutions. Use advanced AI tools to produce high-quality blogs, technical documentation, case studies, and thought leadership pieces.
What you’ll do
- Produce technical content on AI/ML, LLMs, proctoring technology using ChatGPT and Google Gemini assistance
- Create comprehensive whitepapers, case studies, and eBooks on AI in education and assessment
- Develop SEO-optimized blog content using AI writing tools and keyword research platforms
- Write technical documentation explaining AI features, ML models, and platform capabilities
- Create video scripts, webinar content, and presentation materials on AI technology
- Optimize content performance using AI-powered analytics and SQL-based insights
- Manage content calendar and distribution using CMS and marketing automation tools
- Collaborate with product and engineering teams to translate technical features into marketing content
- Implement content personalization strategies using AI recommendation engines
- Track content metrics using Google Analytics, Ahrefs, and data visualization tools
Requirements & qualifications
- AI Writing Tools: ChatGPT, Google Gemini, Claude, Jasper, Writesonic
- SEO: SEMrush, Ahrefs, Surfer SEO, Clearscope for AI-powered optimization
- CMS: WordPress, HubSpot CMS, Contentful, Webflow
- Analytics: Google Analytics 4, Google Search Console, Ahrefs Content Explorer
- Data Skills: SQL for content performance analysis, Excel/Google Sheets
- Technical Understanding: Familiarity with AI/ML concepts, LLMs, cloud technologies
- Content Tools: Grammarly, Hemingway Editor, Copyscape
- Project Management: Asana, Monday.com, Notion for content planning
- Visual Content: Canva, Figma, AI image generation tools (Midjourney, DALL-E)
- Video: Basic video editing, YouTube optimization, webinar platforms
- Understanding of B2B SaaS, EdTech, and HR Tech industries
Marketing Data Analyst (AI & Analytics)
MarketingHybrid / In-office2-4 yearsFull-Time
Analyze marketing data and derive actionable insights using AI tools, SQL, and advanced analytics platforms. Support data-driven decision making for marketing campaigns and strategy.
Marketing Data Analyst (AI & Analytics)
MarketingHybrid / In-office2-4 yearsFull-Time
Analyze marketing data and derive actionable insights using AI tools, SQL, and advanced analytics platforms. Support data-driven decision making for marketing campaigns and strategy.
What you’ll do
- Build marketing dashboards and reports using Tableau, Power BI, Google Data Studio
- Perform SQL queries on marketing databases (PostgreSQL, MySQL, BigQuery) to extract insights
- Use ChatGPT and AI tools for data analysis, pattern recognition, and report generation
- Implement predictive analytics and customer segmentation using machine learning tools
- Analyze campaign performance across channels (Google Ads, LinkedIn, email, social media)
- Create attribution models to understand customer journey and conversion paths
- Develop automated reporting systems using Python, R, or Google Apps Script
- Implement A/B testing frameworks and statistical analysis for marketing experiments
- Use AI-powered BI tools for anomaly detection and trend forecasting
- Collaborate with marketing teams to provide data-driven recommendations
Requirements & qualifications
- Data Analysis: SQL (PostgreSQL, MySQL, BigQuery), Python (pandas, numpy)
- Visualization: Tableau, Power BI, Google Data Studio, Looker
- AI Tools: ChatGPT for data analysis, Google Gemini, Claude for insights
- Analytics Platforms: Google Analytics 4, Adobe Analytics, Mixpanel, Amplitude
- Statistical Analysis: R, Python (scipy, statsmodels), Excel
- Marketing Tools: Google Ads, Facebook Ads Manager, HubSpot, Salesforce
- Cloud Data: Google BigQuery, AWS Redshift, Snowflake
- ETL Tools: Fivetran, Stitch, Apache Airflow for data pipelines
- Excel/Google Sheets: Advanced formulas, pivot tables, macros
- Machine Learning: Scikit-learn, TensorFlow for predictive modeling
- Understanding of marketing metrics, KPIs, and attribution modeling
Pre Sales Consultant (AI Solutions)
SalesHybrid / In-office4-7 yearsFull-Time
Drive technical sales conversations for our AI-powered assessment, proctoring, and document verification solutions. Demonstrate deep understanding of AI/ML technologies, LLMs, and cloud platforms to articulate value propositions to enterprise clients.
Pre Sales Consultant (AI Solutions)
SalesHybrid / In-office4-7 yearsFull-Time
Drive technical sales conversations for our AI-powered assessment, proctoring, and document verification solutions. Demonstrate deep understanding of AI/ML technologies, LLMs, and cloud platforms to articulate value propositions to enterprise clients.
What you’ll do
- Conduct product demonstrations showcasing AI features including ChatGPT integration, Google Gemini capabilities, and ML-driven proctoring
- Create compelling technical proposals and presentations highlighting AI/ML capabilities, cloud infrastructure, and security
- Explain complex AI concepts (LLMs, computer vision, NLP) to non-technical stakeholders in business terms
- Design custom solutions leveraging AI technologies to meet specific client requirements
- Prepare ROI analyses and business cases using SQL-based data insights and AI-powered analytics
- Conduct proof-of-concepts (POCs) demonstrating real-time video proctoring, document verification, and AI assessment features
- Collaborate with product and engineering teams to address technical queries about AI models and cloud architecture
- Present competitive analyses highlighting our AI advantages over traditional assessment platforms
- Use CRM systems (Salesforce, HubSpot) integrated with AI tools for pipeline management and forecasting
- Stay updated on latest AI trends, LLM developments (ChatGPT, Google Gemini, Claude), and EdTech/HR Tech innovations
Requirements & qualifications
- Technical Knowledge: Understanding of AI/ML, LLMs (ChatGPT, Google Gemini), computer vision, NLP
- Cloud Platforms: AWS, Google Cloud Platform, Azure architecture and services
- AI Tools Familiarity: ChatGPT, Google Gemini, Claude, OpenAI APIs, ML frameworks
- Presentation Tools: PowerPoint, Google Slides, Canva, Figma for creating compelling demos
- CRM: Salesforce, HubSpot with AI-powered sales analytics
- Data Analysis: SQL for creating custom reports and insights, Excel for ROI modeling
- Video Conferencing: Zoom, Google Meet, Microsoft Teams for remote demonstrations
- Technical Documentation: Ability to create technical proposals, RFP responses, architecture diagrams
- Understanding of EdTech, HR Tech, and enterprise software sales cycles
- Knowledge of security standards (SOC 2, GDPR, ISO 27001) and compliance requirements
- Familiarity with WebRTC, video streaming technologies, and real-time communication protocols
Solutions Architect (Pre Sales)
SalesHybrid / In-office5-8 yearsFull-Time
Design and architect AI-powered assessment and proctoring solutions for enterprise clients. Bridge the gap between technical capabilities and business requirements while showcasing advanced AI, cloud, and ML technologies.
Solutions Architect (Pre Sales)
SalesHybrid / In-office5-8 yearsFull-Time
Design and architect AI-powered assessment and proctoring solutions for enterprise clients. Bridge the gap between technical capabilities and business requirements while showcasing advanced AI, cloud, and ML technologies.
What you’ll do
- Design end-to-end solution architectures incorporating AI/ML models, cloud infrastructure, and real-time video streaming
- Create technical architecture diagrams showing integration of ChatGPT, Google Gemini, and custom ML models
- Conduct technical discovery sessions to understand client requirements and data infrastructure
- Develop integration strategies for connecting our platform with client LMS, HRIS, and other enterprise systems
- Present cloud architecture solutions (AWS, GCP, Azure) ensuring scalability, security, and compliance
- Design data flow architectures showing how AI processes assessment data, video streams, and document verification
- Create proof-of-concept implementations demonstrating AI capabilities and custom integrations
- Provide technical guidance on API integrations, SSO implementation, and data security measures
- Use SQL and data modeling to design custom reporting and analytics solutions
- Collaborate with sales teams to respond to RFPs with detailed technical specifications
Required skills & technologies
- Cloud Architecture: AWS, Google Cloud Platform, Azure (EC2, Lambda, SageMaker, GKE, AKS)
- AI/ML Platforms: Understanding of LLM deployment, ML model serving, ChatGPT/Google Gemini integration
- Solution Design: Enterprise architecture patterns, microservices, API design (REST, GraphQL)
- Database: SQL (PostgreSQL, MySQL), NoSQL (MongoDB), data warehousing (BigQuery, Redshift)
- Integration: API gateways, ESB, ETL tools, webhook architectures
- Security: OAuth 2.0, SAML, SSO, encryption, compliance standards (SOC 2, GDPR)
- Video Technology: WebRTC architecture, streaming protocols, CDN configuration
- Documentation: Lucidchart, Draw.io, Confluence for architecture diagrams
- DevOps: Docker, Kubernetes, CI/CD pipelines understanding
- CRM/Sales Tools: Salesforce, HubSpot for opportunity management
- Technical writing skills for proposals, RFPs, and technical documentation
Technical Account Manager (AI Products)
SalesHybrid / In-office3-6 yearsFull-Time
Serve as technical liaison between sales and prospective clients, providing technical expertise on AI-powered assessment and proctoring solutions. Support sales process with demonstrations, technical consultation, and solution design.
Technical Account Manager (AI Products)
SalesHybrid / In-office3-6 yearsFull-Time
Serve as technical liaison between sales and prospective clients, providing technical expertise on AI-powered assessment and proctoring solutions. Support sales process with demonstrations, technical consultation, and solution design.
What you’ll do
- Demonstrate AI features including ChatGPT-powered assessments, ML-based proctoring, and document verification
- Explain technical concepts around LLMs, computer vision, cloud infrastructure in business-friendly terms
- Create customized product demonstrations highlighting relevant AI and cloud capabilities
- Support RFP responses with technical content about AI models, security, and infrastructure
- Conduct technical workshops and training sessions for prospective clients
- Use SQL to generate custom reports and analytics for client presentations
- Coordinate with product and engineering teams for technical feasibility assessments
- Provide competitive analysis focusing on AI/ML differentiators
- Manage proof-of-concept implementations and pilot programs
- Maintain CRM (Salesforce/HubSpot) with technical notes and client requirements
Required skills & technologies
- AI/ML Understanding: LLMs (ChatGPT, Google Gemini), machine learning basics, computer vision
- Cloud Knowledge: AWS, Google Cloud, Azure services and deployment models
- Technical Presentation: PowerPoint, Google Slides, live demo capabilities
- CRM: Salesforce, HubSpot for account management and reporting
- Data Skills: SQL for querying and reporting, Excel for data analysis
- Video Technology: Understanding of WebRTC, video streaming, proctoring systems
- API Knowledge: REST APIs, webhooks, integration concepts
- Security Awareness: OAuth, SSO, data encryption, compliance (GDPR, SOC 2)
- Communication Tools: Zoom, Google Meet, Slack for client interactions
- Understanding of SaaS business models and enterprise software
- EdTech or HR Tech industry knowledge preferred
Prompt Engineer
AI/MLHybrid / In-office2-5 yearsFull-Time
Design and optimize prompts for LLM-powered features in our AI assessment, proctoring, and document verification platforms. Create sophisticated prompt strategies using ChatGPT, Google Gemini, Claude, and other LLMs to deliver accurate, contextual, and reliable AI responses.
Prompt Engineer
AI/MLHybrid / In-office2-5 yearsFull-Time
Design and optimize prompts for LLM-powered features in our AI assessment, proctoring, and document verification platforms. Create sophisticated prompt strategies using ChatGPT, Google Gemini, Claude, and other LLMs to deliver accurate, contextual, and reliable AI responses.
What you’ll do
- Design, develop, and optimize prompts for ChatGPT, Google Gemini, Claude, and other LLM platforms
- Implement advanced prompt engineering techniques: few-shot learning, chain-of-thought, prompt chaining, and role-based prompting
- Build and maintain prompt templates for assessment generation, automated grading, and feedback systems
- Develop AI agents using LangChain, LlamaIndex, Semantic Kernel for complex multi-step workflows
- Create prompt testing frameworks to evaluate accuracy, consistency, and reliability of LLM outputs
- Perform A/B testing on prompts and analyze performance metrics (accuracy, precision, recall, F1)
- Work with RESTful APIs from OpenAI, Google AI, Anthropic, Hugging Face, and process JSON responses
- Collaborate with ML engineers to fine-tune models and optimize prompt-model interactions
- Implement retrieval-augmented generation (RAG) systems for context-aware AI responses
- Design conversational AI flows for chatbots and virtual assessment assistants
- Monitor and mitigate AI bias, hallucinations, and ensure ethical AI practices
- Document prompt libraries, best practices, and maintain version control using Git/GitHub
- Perform data cleaning and preparation for prompt training and inference optimization
Required skills & technologies
- Expert-level prompt engineering and prompt testing: tuning, chaining, optimization techniques
- Deep understanding of Generative AI & LLM capabilities: use cases, limitations, best practices
- Hands-on experience building AI agents with LangChain, LlamaIndex, Semantic Kernel, or AutoGPT
- Proficiency with multiple LLM platforms: ChatGPT (GPT-4, GPT-4o), Google Gemini, Claude, LLaMA
- Experience with RESTful APIs and JSON processing (OpenAI API, Hugging Face, Google AI)
- Understanding of core ML algorithms: regression, classification, clustering for context
- Knowledge of NLP fundamentals and text processing techniques
- Model evaluation skills: accuracy, precision, recall, F1-score metrics
- Data cleaning and preparation for training and inference optimization
- Version control with Git/GitHub for prompt library management
- Experience with Python for scripting and automation (preferred)
- Familiarity with Scikit-learn, PyTorch, or TensorFlow (preferred)
- Strong awareness of AI ethics, bias detection, and responsible AI practices
- Excellent written communication for documenting prompts and guidelines
- Experience with RAG (Retrieval-Augmented Generation) and vector databases (Pinecone, Weaviate) is a plus
Technical proficiencies
- LLM Platforms: ChatGPT (GPT-4, GPT-4o, GPT-3.5), Google Gemini, Claude (Anthropic), LLaMA 2/3
- AI Frameworks: LangChain, LlamaIndex, Semantic Kernel, Haystack
- APIs: OpenAI API, Google AI API, Anthropic API, Hugging Face Transformers
- Programming: Python (automation/testing), JavaScript/TypeScript (integrations)
- Tools: Prompt testing platforms, LangSmith, PromptPerfect, AI evaluation tools
- Vector Databases: Pinecone, Weaviate, Chroma, FAISS (for RAG)
- Cloud: AWS (Bedrock, SageMaker), Google Cloud (Vertex AI), Azure OpenAI Service
- Version Control: Git, GitHub for prompt versioning and collaboration
- ML Libraries: Scikit-learn, PyTorch, TensorFlow (basic understanding)
Key competencies
- Advanced prompt engineering: zero-shot, few-shot, chain-of-thought, tree-of-thought
- Prompt optimization: temperature tuning, token management, context window optimization
- Error analysis: identify and mitigate hallucinations, bias, inconsistencies
- Testing methodologies: systematic evaluation of prompt performance & reliability
- AI agent design: multi-step reasoning, tool use, autonomous decision-making
- Context engineering: effective system prompts and context management strategies
Senior AI/ML Engineer
AI/MLHybrid / In-office5-8 yearsFull-Time
We’re seeking an experienced AI/ML Engineer to develop and deploy cutting-edge AI solutions for our assessment, remote proctoring, and document verification platforms. You’ll work with advanced LLMs, computer vision, and cloud technologies to build intelligent systems.
Senior AI/ML Engineer
AI/MLHybrid / In-office5-8 yearsFull-Time
We’re seeking an experienced AI/ML Engineer to develop and deploy cutting-edge AI solutions for our assessment, remote proctoring, and document verification platforms. You’ll work with advanced LLMs, computer vision, and cloud technologies to build intelligent systems.
What you’ll do
- Design and implement AI/ML models using Google Gemini, ChatGPT API, and other LLM frameworks for intelligent assessment and proctoring systems
- Build Agentic AI systems and autonomous agents using N8N, LangChain, and LlamaIndex for workflow automation and intelligent decision-making
- Develop computer vision algorithms for real-time video proctoring, facial recognition, and document verification using TensorFlow, PyTorch
- Build and optimize NLP models for automated grading, plagiarism detection, and content analysis
- Implement advanced image detection systems for detecting anomalies during remote assessments
- Deploy ML models on cloud platforms (AWS SageMaker, Google Cloud AI Platform, Azure ML)
- Integrate ChatGPT and Google Gemini APIs for conversational AI features in assessment platforms
- Design data pipelines using Apache Kafka, Airflow for real-time data processing
- Create AI agent workflows using N8N for automated assessment generation, grading, and feedback loops
- Implement MLOps practices using Kubernetes, Docker, and CI/CD pipelines
- Optimize model performance for low-latency video streaming and real-time inference
Required skills & technologies
- Strong expertise in LLM integration (ChatGPT, Google Gemini, Claude, LLaMA 2/3)
- Agentic AI Development: Expertise in building autonomous AI agents, multi-agent systems, and agentic workflows
- N8N: Hands-on experience building AI automation workflows, agent orchestration, and LLM integrations using N8N
- Advanced knowledge of machine learning frameworks: TensorFlow, PyTorch, Scikit-learn
- Proficiency in Python, with experience in FastAPI, Flask for ML API development
- AI Agent Frameworks: LangChain, LlamaIndex, AutoGPT, CrewAI for building intelligent agents
- Experience with computer vision libraries: OpenCV, YOLO, MediaPipe for video analysis
- Cloud platforms: AWS (Lambda, SageMaker, EC2), GCP (Vertex AI, Cloud Functions), Azure
- Real-time video streaming technologies: WebRTC, FFmpeg, GStreamer
- Database expertise: MS SQL Server, PostgreSQL, MongoDB, Redis, Vector databases (Pinecone, Weaviate)
- Experience with prompt engineering and fine-tuning LLMs
- Knowledge of SQL (MS SQL Server preferred) and NoSQL databases for data access and management
- Frontend integration: Angular for building AI-powered user interfaces and dashboards
- Understanding of NAT traversal, TURN/STUN servers for peer-to-peer video streaming
- Experience with containerization (Docker, Kubernetes) and microservices architecture
Full Stack Developer (AI-Focused)
EngineeringHybrid / In-office3-6 yearsFull-Time
Join our development team to build next-generation AI-powered assessment and proctoring platforms. You’ll integrate cutting-edge AI technologies with modern web frameworks to create seamless user experiences.
Full Stack Developer (AI-Focused)
EngineeringHybrid / In-office3-6 yearsFull-Time
Join our development team to build next-generation AI-powered assessment and proctoring platforms. You’ll integrate cutting-edge AI technologies with modern web frameworks to create seamless user experiences.
What you’ll do
- Develop responsive web applications integrating ChatGPT, Google Gemini for AI-powered features
- Build Agentic AI workflows and autonomous agents using N8N for intelligent automation and multi-step reasoning
- Build real-time video proctoring interfaces using WebRTC, Socket.io, and cloud streaming services
- Implement AI-driven document verification systems with OCR and image processing capabilities
- Create RESTful and GraphQL APIs for AI model integration and data access
- Design and optimize SQL/NoSQL databases (MS SQL Server, PostgreSQL, MongoDB, Redis) for high-performance applications
- Integrate LLM APIs for automated assessment generation, grading, and feedback systems
- Develop AI agent orchestration systems using N8N, LangChain, and LlamaIndex for complex workflows
- Develop cloud-native applications using AWS, Google Cloud Platform, or Azure
- Implement secure authentication and authorization using OAuth 2.0, JWT, and SSO
- Build CI/CD pipelines and deploy containerized applications using Docker and Kubernetes
Required skills & technologies
- Frontend: Angular (required), React.js, Next.js, Vue.js, TypeScript, Tailwind CSS
- Backend: Node.js, Python (FastAPI/Django), .NET Core, or Java Spring Boot
- Agentic AI: Experience building autonomous AI agents, multi-agent systems, and intelligent automation workflows
- N8N: Hands-on experience with N8N for workflow automation, AI agent orchestration, and LLM integrations
- AI Integration: ChatGPT API, Google Gemini API, OpenAI SDKs, LangChain, LlamaIndex for agentic workflows
- Database: MS SQL Server (required), PostgreSQL, MySQL, NoSQL (MongoDB, DynamoDB), Redis caching
- Cloud Platforms: AWS (Lambda, EC2, S3, CloudFront), GCP, Azure
- Video Streaming: WebRTC, Agora.io, Twilio Video, AWS IVS
- Real-time Communication: Socket.io, WebSockets, Server-Sent Events
- DevOps: Docker, Kubernetes, Jenkins, GitHub Actions, Terraform
- API Development: REST, GraphQL, gRPC
- Experience with prompt engineering and LLM integration patterns
- Understanding of NAT/firewall traversal for P2P video connections
Cloud Infrastructure Engineer (AI/ML Focus)
EngineeringIn-office / Hybrid4-7 yearsFull-Time
Build and maintain scalable cloud infrastructure for AI-powered assessment and proctoring platforms. Design systems that support real-time video streaming, ML model deployment, and high-traffic applications.
Cloud Infrastructure Engineer (AI/ML Focus)
EngineeringIn-office / Hybrid4-7 yearsFull-Time
Build and maintain scalable cloud infrastructure for AI-powered assessment and proctoring platforms. Design systems that support real-time video streaming, ML model deployment, and high-traffic applications.
What you’ll do
- Design and deploy cloud infrastructure for AI/ML workloads on AWS, GCP, or Azure
- Deploy and manage N8N infrastructure for Agentic AI workflows and autonomous agent orchestration
- Implement auto-scaling infrastructure for video streaming and real-time proctoring services
- Set up ML model deployment pipelines using AWS SageMaker, Google Vertex AI, or Azure ML
- Configure infrastructure for AI agent systems, including N8N, LangChain services, and vector databases
- Configure CDN and edge computing solutions for low-latency video delivery (CloudFront, Cloudflare)
- Implement monitoring and observability using Prometheus, Grafana, ELK Stack, or Datadog
- Design secure network architecture with VPC, security groups, and NAT gateways
- Optimize database performance for high-throughput SQL (MS SQL Server) and NoSQL workloads
- Implement Infrastructure as Code using Terraform, CloudFormation, or Pulumi
- Set up CI/CD pipelines for ML models, AI agents, and microservices deployment
Required skills & technologies
- Cloud Platforms: AWS (EC2, Lambda, SageMaker, ECS/EKS), GCP (GKE, Vertex AI), Azure
- Agentic AI Infrastructure: Experience deploying and managing autonomous AI agent systems and multi-agent frameworks
- N8N Deployment: Hands-on experience deploying N8N workflows, managing N8N infrastructure, and scaling agent orchestration systems
- Container Orchestration: Kubernetes, Docker Swarm, AWS ECS/Fargate
- Infrastructure as Code: Terraform, AWS CloudFormation, Ansible, Pulumi
- CI/CD: Jenkins, GitLab CI, GitHub Actions, ArgoCD
- Monitoring: Prometheus, Grafana, CloudWatch, Azure Monitor, Datadog
- Databases: MS SQL Server (required), PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, Vector databases (Pinecone, Weaviate)
- Video Streaming: AWS IVS, Agora, WebRTC infrastructure, TURN/STUN servers
- Security: IAM, Secret Management (Vault, AWS Secrets Manager), SSL/TLS
- Networking: VPC, Load Balancers, NAT Gateway, VPN, CDN configuration
- ML Infrastructure: MLflow, Kubeflow, SageMaker Pipelines
- Scripting: Python, Bash, PowerShell
- Frontend deployment: Experience deploying Angular applications and SPAs
Backend Developer (AI/LLM Integration)
EngineeringRemote / Hybrid3-5 yearsFull-Time
Develop robust backend systems that power our AI-driven assessment and proctoring solutions. Focus on integrating LLMs, building scalable APIs, and managing complex data workflows.
Backend Developer (AI/LLM Integration)
EngineeringRemote / Hybrid3-5 yearsFull-Time
Develop robust backend systems that power our AI-driven assessment and proctoring solutions. Focus on integrating LLMs, building scalable APIs, and managing complex data workflows.
What you’ll do
- Build RESTful and GraphQL APIs integrating ChatGPT, Google Gemini, and other LLM services
- Design and implement Agentic AI systems using N8N for autonomous workflows, multi-step reasoning, and intelligent automation
- Develop microservices architecture for AI-powered assessment and proctoring features
- Build AI agent backends using LangChain, LlamaIndex, and N8N for complex agent orchestration
- Implement real-time data processing pipelines for video analytics and user behavior tracking
- Design and optimize database schemas for SQL (MS SQL Server) and NoSQL (MongoDB) databases
- Create secure authentication systems with OAuth 2.0, JWT, and multi-factor authentication
- Integrate third-party AI services and APIs (OpenAI, Google AI, AWS Rekognition)
- Build event-driven architectures using message queues (RabbitMQ, Kafka, AWS SQS)
- Implement caching strategies using Redis and CDN for performance optimization
- Develop automated testing frameworks and maintain code quality standards
Requirements & qualifications
- Programming: Python (FastAPI, Django, Flask), Node.js, or Java/Kotlin
- Agentic AI: Expertise in building autonomous AI agents, multi-agent systems, and agentic workflows
- N8N: Hands-on experience with N8N for AI workflow automation, agent orchestration, and backend integrations
- LLM Integration: ChatGPT API, Google Gemini, OpenAI SDK, LangChain, LlamaIndex, Anthropic Claude
- Databases: MS SQL Server (required), PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch, Vector databases
- Cloud Services: AWS (Lambda, API Gateway, S3, RDS), GCP, Azure
- API Development: REST, GraphQL, gRPC, WebSocket
- Message Queues: RabbitMQ, Apache Kafka, AWS SQS/SNS
- Caching: Redis, Memcached, CloudFront
- Testing: Jest, Pytest, JUnit, Postman, K6 for load testing
- DevOps: Docker, Kubernetes, CI/CD pipelines
- Security: OWASP standards, data encryption, secure API design
- Experience with SQL query optimization and database indexing strategies (MS SQL Server preferred)
- Frontend integration: Experience building APIs for Angular applications
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