My Client is hiring a Principal AI Architect to help shape and build the next generation of their AI-powered products. This is a high-impact, player-coach role where you’ll operate at the intersection of hands-on engineering and technical leadership.
You’ll personally build core components of their agentic AI platform while also guiding architecture, governing delivery, and partnering closely with product and leadership. This is a unique opportunity to own AI architecture end-to-end and have a direct impact on product direction and innovation.
What You’ll Do
Build (Hands-On)
- Design and develop core components of our agentic AI product (RAG pipelines, LLM integrations, agent workflows)
- Prototype and ship production-grade features using frameworks like LangChain, LangGraph, Dify, or similar
- Make full-stack technical decisions across backend, APIs, data, and cloud infrastructure
Lead (Player-Coach)
- Oversee and guide the work of our external delivery partner
- Conduct architecture and code reviews to ensure quality and alignment
- Serve as the key technical escalation point across teams
Own (Architecture & Strategy)
- Define and drive the AI architecture vision (tooling, platforms, integrations)
- Partner with leadership on AI strategy, governance, and build-vs-buy decisions
- Translate product direction into scalable technical solutions
What We’re Looking For
- 10+ years of experience and proven track record of developing and designing AI-powered products across the full lifecycle – from architecture and build through to production and iteration.
- Proven track record building and shipping AI-powered products end-to-end
- Deep hands-on experience with agentic AI frameworks and orchestration tooling (LangChain, LangGraph, Dify, BeeAI, Flowise, Braintrust or equivalent) – beyond LLM API integration.
- Identity management, authentication, RBAC and other access management solution knowledge for AI agents.
- Ability to design and govern distributed, cloud-native architectures — defining integration patterns, API contracts, and data models at an organisational level.
Strong knowledge of:
- RAG, vector databases, prompt orchestration, tool use, memory architectures
- LLM platforms (OpenAI, Anthropic, Bedrock, Azure AI)
- Experience operating as a player-coach, balancing hands-on build with technical oversight
- Ability to design and govern cloud-native, distributed systems
- Strong communicator who can engage both engineers and senior stakeholders
Nice to Have
- Experience with multi-agent systems or MCP (Model Context Protocol)
- Exposure to AI governance and responsible AI practices
Why This Role
- Opportunity to own AI architecture at a company level
- Build and ship cutting-edge agentic AI products
- High visibility with leadership and direct impact on product strategy
- Operate in a true builder + strategist role
If you’re excited about building real-world AI systems and want to operate at both the technical and strategic level, we’d love to connect.
