Description

You will design and implement agentic AI solutions, including single-agent and multi-agent systems. You translate business problems into agent goals, workflows, and tool chains. You lead the architecture and design of LLM-orchestrated systems with memory, planning, and decision logic. You integrate AI agents with enterprise platforms, APIs, and data sources. You apply AI governance, risk, and control frameworks across agent lifecycles. You advise clients on scalability, security, and operationalization. You support solutioning, PoCs, and MVPs aligned to client scope documents. You mentor junior team members and review agent designs and code.

Responsibilities

• Design and implement agentic AI solutions using LangGraph and RAG.
• Lead architecture of LLM-orchestrated systems with memory and planning.
• Integrate agents with enterprise platforms, APIs, and data sources.
• Apply AI governance and risk frameworks across agent lifecycles.
• Mentor junior engineers and review agent designs and code.

Required Skills

• 5+ years of experience in AI/ML engineering.
• Strong knowledge of Google Cloud Platform (GCP).
• Proficiency in Python.
• Experience with LangGraph for agent orchestration.
• Hands-on experience with Retrieval-Augmented Generation (RAG).
• Deep Learning (DL) and Machine Learning (ML) fundamentals.
• Experience integrating with enterprise platforms and APIs.

Preferred Skills

• Experience with multi-agent systems and tool chains.

Key Skills

Education

Any Gradute