Description

You will lead architecture design for multi-agent systems, LLM orchestration, and AI automation workflows. You define and maintain the agentic AI engineering stack, including frameworks, CI/CD pipelines, testing, monitoring, and deployment practices. You own technical design and delivery for AI orchestration use cases across multiple client implementations.

Responsibilities

• Build reusable agent components, prompt templates, and tool integration libraries.
• Evaluate and select LLM providers based on performance, cost, and latency.
• Bridge the gap between data science models and production systems for scalability.
• Lead and mentor senior engineers through code reviews and technical guidance.
• Establish operational practices including documentation, runbooks, and monitoring.

Required Skills

• Strong experience in Python for AI/ML engineering and system development.
• Deep expertise in MLOps, including model deployment, monitoring, and lifecycle management.
• Hands-on experience building Agentic AI systems and Generative AI applications.
• Strong understanding of Large Language Models (LLMs) and orchestration frameworks.
• Experience with cloud platforms: AWS, Azure, or GCP.
• Familiarity with LangChain and LangGraph for building AI workflows.
• Experience designing scalable AI systems using microservices and APIs.
• Knowledge of RAG architectures, vector databases, and semantic search systems.
• 10+ years of experience with a Bachelor's or Master's degree in Computer Science or Engineering.

Key Skills

Education

Any Graduate