Agentic AI Engineer

Job Description

Agentic AI Engineer

Must-Have

• 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms.
• Proven experience developing and delivering large-scale AI solutions, Agentic AI systems, AI platforms, or multi-agent frameworks in enterprise environments.
• Deep understanding of the Agentic AI ecosystem including agent orchestration, planning, reasoning, tool calling, memory management, retrieval systems, and autonomous workflows.
• Hands-on expertise building AI applications using frameworks and platforms such as Google ADK, LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar agentic frameworks.
• Strong experience designing scalable orchestration layers, tool libraries, context management frameworks, observability solutions, and governance controls for AI systems.
• Expertise in Retrieval-Augmented Generation (RAG), vector databases, embeddings, enterprise knowledge systems, and document intelligence platforms.
• Deep understanding of AI observability, monitoring, evaluation frameworks, model governance, security, and responsible AI principles.
• Strong communication and stakeholder management skills, with demonstrated ability to effectively communicate with and influence senior technology leaders.

Good-to-Have

• Working knowledge of Glean or similar enterprise document intelligence and knowledge management platforms.
• Experience developing enterprise AI accelerators, reusable frameworks, and agentic platforms supporting large-scale business adoption.
• Experience with multi-cloud AI ecosystems including Google Cloud, Azure AI, AWS AI, and OpenAI-based solutions.
• Exposure to AI governance, model risk management, compliance, privacy, and enterprise security controls.

Key Roles & Responsibilities

• Evolve agent frameworks into a scalable, extensible, and enterprise-grade agentic platform aligned with future business needs.
• Define and own the end-to-end development covering orchestration, tool integration, memory management, context management, document intelligence, observability, security, and governance.
• Provide technical leadership and hands-on engineering guidance across all components of the Agentic AI platform.
• Design reusable services, frameworks, and platform capabilities to accelerate onboarding of new AI use cases and business domains.
• Establish development standards, reference patterns, engineering best practices, and strategic direction for platform evolution.
• Evaluate emerging Agentic AI technologies, frameworks, and industry trends, recommending strategic enhancements to the platform.
• Mentor engineering teams and serve as a thought leader for enterprise Agentic AI strategy and platform evolution.