AI Engineering Lead

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Qualifications

• 7+ years in AI / ML engineering, with 3+ years in GenAI or LLM-based systems.
• Proficiency in Python and hands-on experience with LangChain, LangGraph, and OpenAI APIs.
• Deep understanding of RAG, multi-agent orchestration, and prompt engineering.
• Experience deploying AI solutions on Azure, AWS, and Google Cloud Platform.
• Familiarity with enterprise AI governance, risk frameworks, and security standards.

Responsibilities

Design and implement RAG architecture patterns, multi-agent systems, and LLM interfacing pipelines

Apply structured prompt frameworks (e.g., RISEN) for task-specific tuning and ethical content generation

Architect and deploy multi-agent systems for enterprise workflows, including decision trees, dynamic orchestration, and fallback logic

Compare and benchmark GenAI frameworks (LangChain vs LangGraph) for performance, flexibility, and maintainability

Ensure adherence to AI risk management policies (AEMP80, AENB80) and GenAI certification standards

Seniority Level

Mid-Senior level

Employment Type

Full-time

Job Function

Engineering and Information Technology

Industries

Software Development

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