Applied AI Architect

Overview

In this role you will shape production-grade, multi-agent AI systems for demanding clients, acting as a trusted adviser alongside customer architects. You’ll set technical standards, run discovery and architecture reviews, and translate complex trade-offs for both engineers and business sponsors. You’ll pair hands-on design with coaching to build reusable AI architectures and maintain reliable, observable systems at scale. This is a frontline, customer-facing technical leadership role that drives impactful AI deployments.

Pay / Benefits

• Quarterly profit share
• Career development programs
• Flexible/remote working
• Pension and private healthcare
• Wellbeing programs
• Educational assistance and certifications

Responsibilities

• Advise customer AI architects and engineers to shape design decisions
• Run discovery, workshops and architecture reviews with stakeholders
• Co-design multi-agent architectures including orchestration, memory, routing and guardrails
• Create reference implementations, evaluation suites and accelerators for customer use
• Address production challenges such as hallucination, tool failures, latency and cost
• Own the technical architecture and standards for complex engagements
• Define evaluation and observability strategies (eval suites, tracing, guardrails, monitoring)
• Mentor Applied AI Consultants and Associates on advanced engineering practices
• Contribute reusable architectures and accelerators to Version 1’s toolkit
• Stay current with agent frameworks and models to inform decisions

Key requirements

• 10–15+ years in software engineering with 5+ years in designing and architecting systems
• 2+ years hands-on experience architecting and running AI/agentic systems in production
• Proven track record in client-facing or consulting roles advising engineering teams
• Direct experience designing multi-agent architectures: orchestration, tool use, memory, routing, guardrails and agent-to-agent communication
• Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen or similar tooling, plus MCP or comparable protocols
• Strong grounding in evaluation, observability and reliability for AI systems (eval suites, tracing, guardrails, monitoring, incident response)
• Hands-on experience with Claude API, Claude Code, MCP, GitHub AI tooling or equivalent in production
• Degree in a related field or equivalent practical experience
• Comfort with solving complex, post-demo production challenges
• Ability to advise and guide customer teams rather than only delivering internally
• Strong client-facing communication
• Trusted advisor mindset
• Collaborative and influential leadership
• LangGraph
• Microsoft Foundry
• AWS Bedrock

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