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Tier-1 employer plus mid-level role, but specialized GenAI skillset reduces candidate pool.
Requires deep LLM, RAG, vector DB, and prompt engineering expertise, limiting cross-industry transferability.
Explicit 5+ years plus 2–3 years GenAI and many mandatory LLM and deployment skills.
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Design, develop, and maintain end-to-end Generative AI and agentic AI applications involving LLMs, multi-agent systems, and RAG pipelines.
Implement and optimize AI workflows with advanced prompt engineering and testing frameworks to ensure model quality, safety, and efficiency.
Collaborate with cross-functional teams and document experiments while staying updated on GenAI technologies and frameworks.
5+ years total IT experience with 2–3 years specifically in AI/ML or Generative AI development.
Hands-on experience deploying LLM-based or agentic AI applications in production or pilot environments.
Proficiency in Python and frameworks/tools including LangChain, LlamaIndex, CrewAI, LangGraph, and prompt evaluation tools like TruLens or LangSmith.
Experience with vector databases (FAISS, Pinecone, Chroma, Milvus) and at least one major cloud AI platform (Azure, AWS, GCP, OCI).
Has proven expertise in building complex AI systems utilizing multi-agent frameworks and advanced retrieval-augmented generation pipelines.
Comfortable with rigorous testing, performance monitoring, and optimization of GenAI models using sophisticated prompt engineering and automated evaluation tools.
Experienced in collaborating within multi-disciplinary teams while maintaining thorough documentation and continuous learning in emerging GenAI tools and models.