Wadhwani Foundation
· AI Team Role: Senior Full Stack AI Engineer Client: Wadhwani Foundation YOE-5–7 year’s 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 GenAI & LLM Systems Production deployment of LLMs — Gemini, Azure OpenAI, Groq, open-source models at scale RAG & Agentic Pipelines LangGraph multi-agent orchestration, LlamaIndex RAG, MCP integrations 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 Core (required): Python
· FastAPI
· LangGraph
· LlamaIndex
· Azure OpenAI
· RAG / Vector DBs
· MCP
· Multimodal AI 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 B.
Tech / M.
Tech / M.
S. from a premier engineering institution — IITs, NITs, IIITs, or equivalent top-tier colleges. We value the rigour and problem-solving foundation that comes with this background. Exceptional candidates with non-traditional paths but strong production AI experience will also be considered. 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 setting -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? Send your resume along with a brief note on a GenAI project you're proud of.

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