Generative AI Engineer
Skills
About the role
This is a senior full-time hybrid GenAI and LLM engineering role based in Bengaluru, India. You'll build production AI applications and improve their prompts, evaluations, guardrails, retrieval, observability, and reliability.
What you’ll do
- Develop and tune LLM applications for business use cases.
- Design prompts for dependable and consistent model behavior.
- Create evaluations covering quality, relevance, groundedness, and performance.
- Build custom guardrails for domain-specific AI systems.
- Use LangSmith, MLflow, or similar tools to diagnose and improve applications.
- Develop and optimize RAG pipelines, embeddings, and context retrieval.
- Use model frameworks and APIs to deliver scalable AI solutions.
- Move solutions from proof of concept into production with engineering and business partners.
What they’re looking for
- At least 6 years of software, AI, or machine-learning engineering experience.
- Strong Python development skills.
- Hands-on experience delivering GenAI or LLM applications.
- Experience with prompt optimization, LLM evaluations, and custom guardrails.
- Experience with LLM observability and debugging tools such as LangSmith or MLflow.
- Knowledge of RAG, embeddings, vector databases, and frameworks such as LangChain, LangGraph, or LlamaIndex.
- Experience with OpenAI, Anthropic, Gemini, Azure OpenAI, or open-source models.
Nice to have
- Experience with AI agents or agentic systems.
- Knowledge of MCP.
- Experience with Docker, Kubernetes, and cloud platforms.
- Understanding of prompt injection, hallucination prevention, and LLM security.
What’s on offer
- Full-time permanent employment.
- Hybrid work based in Bengaluru, India.
- The posting describes a senior role focused on production-ready GenAI systems.
Questions about this role
Where is this job based?
The role is hybrid and based in Bengaluru, India.
How much experience is required?
The posting asks for 6 to 8 years in the listing and at least 6 years in the description.
What technologies are important?
Python, LLMs, RAG, vector databases, LangChain, LangGraph, LlamaIndex, LangSmith, MLflow, and model APIs are emphasized.
Is experience with AI agents required?
AI agent experience is listed as a desirable qualification rather than a core requirement.
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