Job Summary

Design and implement scalable agentic AI architectures for enterprise use cases.
Build multi‑agent systems using LangChain, LangGraph, and Google ADK.
Architect and optimize advanced RAG pipelines with high retrieval precision.
Lead LLM strategy, including model selection and cost‑performance optimization.
Develop Python‑based systems with strong engineering and system‑design principles.
Optimize vector databases for latency, relevance, and scalability.
Implement advanced prompt engineering and agent reasoning workflows.
Design and expose AI capabilities via APIs and microservices architectures.
Define and execute LLM evaluation frameworks for quality and reliability.
Ensure adherence to security, privacy, and Responsible AI standards.

Key Responsibilities

1. To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity.
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.

Skill Requirements

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Other Requirements

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