Work on AI at scale
Systems behind 40M+ assessments, not a demo.
Build your career in AI at Splashgain.
Join our engineering, AI, product or customer success teams. Build software that universities and enterprises use for assessments and document verification.
Real AI, running at real scale
A fast-growing team serving clients in India and abroad, looking for people who want to build, share ideas and keep learning.
Own outcomes, not tickets
A lean team that works close to the customer and sees its work used.
Patent-grade engineering
Our Onscreen Marking System holds an India and Worldwide PCT patent.
Global customer base
Multi-language, multi-region problems from day one, across 17+ countries.
How the job actually works
Remote-First Culture
Work from anywhere, with flexible hours.
Learning & Development
Continuous learning and skill programmes.
Work-Life Balance
Flexible schedules and time off.
What happens after you write to us
- 1
AI Telephonic Interview
A short screening call with our AI interviewer, on any phone, at a time that suits you.
- 2
AI Video Interview
Role-specific questions answered on video, reviewed by our team.
- 3
Interview / Technical Test
An interview with team members, or a practical test of your skills.
- 4
Offer
Final decision and offer discussion.
9 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.
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
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
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
What you would actually be building here
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