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Gen AI Tech Lead
Pune · Director
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What we know about this role
HIGH
KPMG India is actively reviewing profiles and moving candidates through the pipeline right now.
First 72 hours
Window passed - posted 36d agoEarly applicants get seen before the pile builds.
Reposted role
This role was posted earlier, closed, and has now reopened - the company is accepting candidates again.
First posted May 19, 2026
Skills required
14 listedYou almost certainly match several of these already. Unlock your skill map to see the matches, the gaps, and what to fix first.
Job description
We are seeking a highly skilled and experienced Lead GenAI Developer with 12+ years of relevant experience to join our team. The ideal candidate will have a strong technical foundation in Python and AI/ML, with a proven track record of delivering scalable, production-grade enterprise solutions. This role requires hands-on expertise in Generative AI technologies, solution architecture, and cloud deployment, particularly on Azure.
- Technical Leadership: Lead the design and development of GenAI-powered solutions. Provide technical direction to the team and ensure alignment with architectural standards and business goals.
- GenAI Expertise:
- Hands-on experience with LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face, LangChain, etc.)
- Ability to fine-tune, prompt-engineer, and integrate LLMs into enterprise applications.
- Stay updated with the latest trends in Generative AI and apply them to solve real-world problems.
- Python Development:
- Strong coding skills in Python.
- Experience with API development, optimization, debugging, and root cause analysis.
- Ability to resolve issues at the application and network level.
- Solution Architecture:
- Design low-level application components aligned with high-level architecture.
- Ensure security, performance, and compliance (e.g., pen-testing readiness).
- Translate business requirements into scalable technical solutions.
- Demo & Documentation:
- Lead solution demos to stakeholders and business users.
- Maintain detailed technical documentation including architecture diagrams, data flows, and deployment guides.
- Experience with vector databases (e.g., FAISS, Pinecone, Azure Cognitive Search).
- Familiarity with MLOps practices and tools.
- Exposure to responsible AI practices and model evaluation techniques.
- Strong communication and stakeholder management skills.
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