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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and productionize enterprise-grade Generative AI, RAG, and Agentic AI solutions using LLMs, vector databases, and orchestration frameworks.
Build and optimize multi-agent workflows including planning, reasoning, tool calling, memory management, and deployment using cloud platforms (Azure/AWS) and containerization (Docker).
Collaborate with AI Architects and technical teams to translate business requirements into scalable AI applications, while owning implementation, integration, evaluation, and monitoring of AI systems.
Minimum Requirements
Strong hands-on experience with Python backend development including FastAPI and REST APIs.
Proven experience in Generative AI & LLM application development, specifically Retrieval-Augmented Generation (RAG) pipelines and integration with LLM providers such as OpenAI, Anthropic, or Google Gemini.
Experience building Agentic AI workflows using tools like LangGraph or LangChain, including multi-agent system orchestration.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in productionizing scalable AI applications involving LLMs, vector databases, and multi-agent orchestration in cloud environments.
Skilled at converting business requirements to practical AI solutions and building robust AI guardrails, evaluation frameworks, and responsible AI practices.
Able to work closely with architects and technical leads, independently implement features, optimize AI performance and cost, and stay updated on emerging LLM and Agentic AI technologies.