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Tier-1 brand, mid-level AI role, metro location, and popular LLM skills heighten candidate competition.
Highly specialized generative AI, agentic systems, and vector DB expertise limits cross-industry transferability.
Multiple mandatory LLM, RAG, LangChain, vector DB, cloud, and deployment requirements enforce strict filtering.
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Design and build enterprise-scale AI systems including LLM-powered applications, agentic workflows, and backend services for measurable business impact.
Develop Retrieval-Augmented Generation (RAG) solutions and multi-agent workflows, integrating with cloud platforms and enterprise APIs.
Implement evaluation frameworks, observability, security, privacy, and Responsible AI principles in production AI solutions.
Strong Python backend engineering skills with experience in frameworks like FastAPI or Flask.
Experience building and deploying LLM-based applications, RAG systems, and agentic workflows.
Proficiency with cloud platforms (Azure, AWS, or GCP), containerization (Docker), and orchestration tools (Kubernetes).
Work Experience Required: Not explicitly mentioned in the JD.
Experience working with orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
Knowledge of data engineering concepts including building data pipelines and managing vector databases.
Ability to apply software engineering best practices, ensure secure and ethical AI deployment, and collaborate effectively in cross-functional teams.