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Tier-1 brand, remote option, metro location and broad GenAI requirements drive high competition.
Specialized GenAI, agentic frameworks and vector DB expertise reduces cross-industry transferability.
Multiple mandatory GenAI frameworks, vector DB, LLMOps and cloud deployment skills increase shortlisting rigor.
Design, build, and deploy generative AI applications including RAG, Agents, and Multi-Agent Systems from prototype to production.
Own key features or components ensuring they are efficient, maintainable, and reliable, contributing to system design and technical decisions.
Mentor junior engineers, review code, and collaborate across teams to translate business needs into scalable AI-powered solutions.
Strong experience with generative AI frameworks (e.g., LangChain, LlamaIndex) and agentic frameworks (e.g., PydanticAI, LangGraph).
Hands-on experience building RAG pipelines with vector databases like FAISS, Pinecone, or Weaviate.
Proficiency in Python software engineering including CI/CD, testing, version control, and deploying AI on cloud platforms (AWS, Azure, GCP).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in independently solving complex technical problems related to generative AI systems.
Able to lead and mentor junior engineers while maintaining engineering best practices and code quality.
Comfortable working in fast-paced, dynamic environments collaborating with cross-functional teams including product managers and data scientists.