Principal AI Architect

About the Role

Principal AI Architect / Tech Delivery Head

You will serve as the senior-most technical leader—owning system architecture, research-to-production translation, engineering quality, and technical governance. Working alongside applied scientists, engineers, data teams, and product leaders, you will define architectural patterns, ensure reliability, and guide the creation of novel multi-agent capabilities.

This is a hands-on technical leadership role requiring deep expertise in LLMs, distributed systems, agent frameworks, and scalable AI infrastructure.

Key Responsibilities

• Architect the Multi-Agent System:

  Own the end-to-end architecture for the Central Orchestrator, Master Agents, interoperability standards, and runtime execution models.

• Technical Leadership:

  Set engineering direction, define technical standards, establish best practices, and oversee system reliability and scalability.

• Delivery Ownership:

  Ensure high-quality, timely delivery of R&D prototypes, internal pilots, and platform capabilities.

• Mentorship:

  Coach applied scientists, AI engineers, and platform engineers; elevate engineering rigor and problem-solving depth.

• Cross-Functional Collaboration:

  Work with Product, Data Engineering, MLOps, and Evaluation teams to translate research ideas into robust, deployable systems.

• R&D Decision-Making:

  Drive architectural choices, technology selection, performance optimization, and system-level trade-offs.

• Security & Compliance:

  Ensure architectures meet requirements for sensitive data, hybrid cloud, and enterprise/government operational constraints.

• Technical Review & Governance:

  Lead design reviews, provide high-level code oversight, and ensure long-term architectural coherence.

Qualifications

Experience

• 10+ years of experience in AI/ML engineering, distributed systems, or large-scale software architecture.
• Demonstrated expertise designing and delivering complex multi-component AI systems.
• Prior leadership experience guiding engineering teams (player/coach model).

Technical Expertise

• Deep knowledge of LLMs, agentic systems, and reasoning frameworks.
• Expertise in distributed systems, microservices, event-driven workflows, and hybrid cloud architectures.
• Strong programming background (Python, Go, or similar).
• Experience with model-serving infrastructure, vector databases, orchestration frameworks, and modern MLOps practices.

Soft Skills

• Strong systems thinking and architectural clarity.
• Excellent written and verbal communication.
• Ability to make high-quality technical decisions under ambiguity.

Who You Are

• A hands-on architect who enjoys solving deep technical problems while guiding teams.
• A systems thinker who balances innovation with delivery execution.
• A collaborative leader comfortable navigating research, engineering, and product domains.
• A technical visionary who can design future-proof platforms while enabling rapid iteration.