Job Description :

Wadhwani Foundation AI Team.

Role : Senior Full Stack AI Engineer.

Client : Wadhwani Foundation.

YOE - 5-7 years experience.

India (Remote / Hybrid) | GenAI RAG Multimodal.

ABOUT THE ROLE :

You will be a core engineer on Wadhwani Foundation's lean AI team, building production-grade AI systems that serve millions of learners across India and global markets.

This is not a research role you will own end-to-end delivery of GenAI pipelines, agentic platforms, and multimodal content automation systems that create measurable social impact at scale.

WHAT YOU'LL WORK ON :

1. GenAI & LLM Systems :

- Production deployment of LLMs Gemini, Azure OpenAI, Groq, open-source models at scale.

2. RAG & Agentic Pipelines :

- LangGraph multi-agent orchestration, LlamaIndex RAG, MCP integrations.

3. Multimodal Content Generation :

- AI-driven audio, image & video generation automation frameworks voice cloning, lip sync, I2V pipelines.

RESPONSIBILITIES :

- Design and ship production GenAI systems end-to-end from backend pipelines to user-facing interfaces.

- Build and maintain RAG architectures and multi-agent orchestration systems using LangGraph, LlamaIndex, and related frameworks.

- Develop multimodal AI pipelines for audio, image, and video content generation and automation.

- Architect scalable APIs using FastAPI / Python; integrate with cloud platforms (Azure, AWS).

- Collaborate with internal teams and external vendors to operationalize AI features as shared services.

- Write clean, well-tested, production-ready code with strong engineering discipline.

- Contribute to architectural decisions and help define team best practices.

- Well versed with AI driven development tools Cursor, Claude, Copilot, Replit, etc.

WHAT WE'RE LOOKING FOR :

- 5-7 years of total engineering experience with demonstrable GenAI production deployments.

- Strong Python expertise; experience with FastAPI, async patterns, and REST API design.

- Hands-on with LLM frameworks : LangGraph, LlamaIndex, LangChain, or equivalent.

- Experience with multimodal AI image/audio/video generation, ASR, TTS, or voice models.

- Solid understanding of RAG architectures, vector stores, embeddings, and retrieval strategies.

- Comfortable with cloud-native deployments on GCP, Azure, Runpod.

- Excellent communication and cross-functional collaboration skills.

Ownership mindset you take a feature from ideation to production.

TECH STACK :

1. Core (required) :

- Python FastAPI LangGraph LlamaIndex Azure OpenAI RAG / Vector DBs MCP Multimodal AI.

2. Supporting :

- React / Streamlit MongoDB Docker / CI-CD Git Kubernetes.

NICE TO HAVE :

- Experience with speech / ASR models (Whisper, Sarvam AI, Azure STT) or TTS / voice cloning (VC) pipelines.

- Exposure to multilingual NLP for Indic or global-south languages.

- Prior work in EdTech, social impact, or mission-driven organisations.

- Published projects, open-source contributions, or patents in AI/ML.

EDUCATION :

- Tech / M.

WHY THIS ROLE :

- Work on AI systems with real, measurable impact serving learners across India, Brazil, Mexico, Philippines and Indonesia.

- Operate at the frontier of GenAI RAG, agentic orchestration, multimodal pipelines in a production environment.

- Lean team with high ownership your decisions shape the architecture, not just the code.

- Mission-driven organization backed by decades of grassroots work in skilling and education.

Ready to build AI that actually matters?