AI Architect

Job Summary

We are seeking a Mid-Senior Architect for the Frontier pod. In this role, you will own the design and governance of agentic systems within a domain, setting the quality bar for the pod's build, and acting as the principal technical advisor to both the pod and the client. You will translate complex requirements into scalable AI solutions, govern orchestration and quality, and mentor Frontier Engineers. This position requires deep expertise in Agentic System Architecture, Enterprise Agent Platforms (e.g., Copilot Studio/Agentforce), AI orchestration & state-management patterns, Agentic Test-Framework Design, Knowledge Graph & Ontology Engineering, RAG-at-scale & grounding strategy, MCP/A2A agent protocols, AI security & access controls, and Technical Advisory & Client Engagement. A minimum of 10-20 years of delivery experience with deep AI-systems design experience is required.

About the Role

The mid-senior architect of the Frontier pod. Having graduated from hands-on engineering, the Master owns the design and governance of agentic systems within a domain, sets the quality bar for the pod's build, and is the principal technical advisor to both the pod and the client. Translates complex requirements into scalable AI solutions, governs orchestration and quality, and mentors Frontier Engineers. The connective tissue between engineering execution and enterprise architecture. Works across the three Frontier axes (technical depth, domain expertise and business mindset), asking what the function should look like in an AI era before deciding what to build, and ties the pod's design to the customer outcome.

Key Responsibilities

• Design and deploy custom agents and agentic workflows; govern permissions, context-sharing and data access.
• Architect agentic deployments on enterprise platforms; design trust-layer and cross-agent governance.
• Define AI orchestration architecture and state, tool-calling and failure-mode patterns for the domain.
• Design agentic quality-assurance frameworks: agentic test orchestration and synthetic-data strategy.
• Engineer enterprise knowledge bases, ontologies and retrieval pipelines for agent grounding at scale.
• Translate complex domain requirements into AI functional specifications for the pod.

Qualifications

Core Skills

• Agentic system architecture
• Enterprise agent platforms (Copilot Studio/Agentforce)
• AI orchestration & state-management patterns
• Agentic test-framework design
• Knowledge graph & ontology engineering
• RAG-at-scale & grounding strategy
• MCP/A2A agent protocols
• AI security & access controls
• Technical advisory & client engagement

Competencies

• AI-Native Solution Architecture
• Agentic Engineering & Orchestration
• Context & Retrieval Engineering
• AI Quality & Evaluation Design
• Technical Leadership & Advisory
• Domain Fluency & Contextual Judgment
• Business-Outcome Orientation

Entry and Growth

Experience

10-20 yrs delivery with deep AI-systems design experience.

Entry

Demonstrate independent agentic-system design and domain governance; pass the Frontier CoE assessment at Specialist level.

What Success Looks Like

Builds, ships and permanently owns AI-native systems end to end in a small Frontier pod, and is measured on the customer outcome the pod commits to, not on technical throughput alone.