Sunovaa Tech
AI Engineer
Skills
2 months ago
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Important information
Contract type:
Permanent
Salary:
₹1,500,000 – ₹2,500,000 / year
Location:
Pune, Maharashtra, India
Work mode:
Onsite
Published on:
31 August 2026
What they need
AI Engineer – GenAI / Agentic AI
Location: Pune
Work Mode: Hybrid
Experience: 5+ Years
Job Description
We are looking for an experienced AI Engineer with strong hands-on expertise in Generative AI, NLP, LLMs, RAG, GraphRAG, and Agentic AI.
The ideal candidate should have strong Python programming skills and proven experience in developing and deploying production-grade GenAI applications. The candidate should be comfortable working across the complete AI application lifecycle, from solution design and architecture to development, testing, deployment, and production support.
Key Responsibilities
- Design and develop enterprise-grade Generative AI and LLM-based applications.
- Build and implement RAG and GraphRAG solutions.
- Develop Agentic AI and Multi-Agent systems.
- Implement prompt engineering, prompt optimization, tool calling, memory management, and agent workflows.
- Work with LLMs such as OpenAI GPT, Claude, Gemini, Llama, and Mistral.
- Develop scalable and maintainable applications using Python.
- Work with vector databases and semantic search technologies.
- Implement automated evaluation frameworks to measure AI output and retrieval quality.
- Develop and maintain unit/integration tests using Pytest.
- Use Docker, Git, code reviews, and modern software engineering practices.
- Take ownership of AI solutions from architecture through production deployment and support.
Mandatory Skills
- 5+ years of software engineering / AI engineering experience.
- 2–3+ years of hands-on Generative AI / LLM development.
- 3+ years of NLP experience.
- Strong Python programming experience.
- Hands-on experience with RAG and GraphRAG.
- Strong experience with Agentic AI and Multi-Agent systems.
- Strong Prompt Engineering and Prompt Optimization skills.
- Experience with LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, Semantic Kernel, or similar frameworks.
- Experience with vector databases such as FAISS, Pinecone, ChromaDB, Weaviate, Milvus, or OpenSearch.
- Proven experience developing and deploying production-grade GenAI applications.
Good to Have
- Experience with AWS Bedrock or Azure OpenAI.
- Knowledge of Model Context Protocol (MCP).
- Experience with cloud-based AI platforms.
- CI/CD and DevOps experience.
Preferred Candidate Profile
Candidates with experience as GenAI Engineer, AI Engineer, LLM Engineer, Agentic AI Developer, Applied AI Engineer, AI Application Engineer, or Generative AI Engineer are preferred.
Important: Candidates should have hands-on production experience with GenAI applications and not only POCs, academic projects, or notebooks.
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