AI Architect

Responsibilities:

• Architecting agentic systems for reasoning, planning, tool use, memory, state, recovery, and multi-agent collaboration.
• Designing agent harnesses and execution loops, including context assembly, planning, tool selection, retries, reflection, and human-in-the-loop mechanisms.
• Building sophisticated evaluation frameworks for non-deterministic AI systems, including trajectory, tool-use, groundedness, retrieval, safety, latency, and cost evaluation.
• Architecting RAG and information-retrieval systems, including hybrid/semantic retrieval, ranking, reranking, permissions, context engineering, grounding, and citations.
• Prototyping complex AI behaviors and approaches through production-quality POCs and reference implementations.
• Driving architecture decisions and ensuring implementation remains aligned with the intended AI behavior and quality standards.
• Mentoring senior engineers and acting as a technical authority on AI/ML feasibility, architecture, and engineering decisions.

Requirements:

• 8+ years of experience building production software/ML systems.
• Strong hands-on experience building production-grade Agentic AI / LLM systems.
• Deep understanding of agent harnesses, orchestration, tool calling, state/memory, and execution loops.
• Strong experience with LLM/AI evaluation, RAG evaluation, and measuring non-deterministic systems.
• Strong information retrieval and context engineering experience.
• Excellent Python and software engineering skills.
• Ability to move between research, experimentation, architecture, and production implementation.
• Strong technical communication and ability to influence senior engineering teams through technical depth.