How You’ll Make An Impact

We’re hiring a Principal AI Field Architect to help our enterprise customers put AI to work. You’ll be one of the people who turns AI capabilities into things customers can actually run — bringing the hands-on model expertise and engineering judgment that most enterprise architecture practices are still developing.

Our team builds with AI more than almost any other team in the company. Per person, we’re among the heaviest users of model tokens anywhere in the business, and that’s by design. We don’t build by hand when a model can get us there faster. The skill we care about isn’t typing code; it’s getting AI to build real things well, checking its work, and shipping. If that’s already how you like to work, you’ll fit in here.

You’ll sit inside a team of veteran principal architects and work on our most complex enterprise accounts. That means you’ll be in the room where architecture decisions get made at scale, with direct access to people who have built these practices across our customers. For the right person, it’s an unusually fast path to broadening your architecture and consulting depth alongside your AI engineering edge.

We work in a “Find, Prove, Deliver” model — building AI workflows that solve real data and orchestration problems for our largest accounts.

 What You’ll Do

• Build, hands-on. You'll ship working things in your first few weeks: agents, integrations, and prototypes that run, not concepts on a slide. You'll use AI-assisted development heavily to move quickly, and you'll know how to check what it produces. You'll own technical design, prototyping, and deployment of agentic workflows.
• Tell the story behind the build. Turn what you’ve built into demos, value narratives, and material an executive can follow. On a “Find, Prove, Deliver” team, the prototype and the story around it both matter.
• Partner with technical stakeholders. Work with customer IT teams and engineering leaders to understand their infrastructure, find AI opportunities, and connect agentic capabilities to their business goals. You’ll hold your own in front of senior executives.
• Deploy and optimize models. Set up and manage model deployments across cloud-hosted environments and local deployment frameworks.
• Shape the product. Bring what you learn in the field back to our product and engineering teams, point out gaps in our prebuilt capabilities, and help steer the roadmap.
• Raise the team’s game. Document how we deliver, improve our playbooks, and share what you know.

The Experience You Bring

• Something you taught yourself and built because you wanted to. A side project, a model you ran locally, a system you took apart to understand — ideally one you built with AI and can walk us through: where the model helped, where it was wrong, and how you knew the difference. Demonstrated initiative here weighs more with us than credentials.
• A working habit of building with AI. You reach for AI tools when you build, and you have genuine judgment about them: you prompt well, you catch subtle errors, and you verify before you ship.
• Cloud and API fundamentals. Hands-on experience with at least one major cloud (AWS, GCP, or Azure) and real work with enterprise APIs in production contexts.
• Familiarity with the modern AI stack. Practical experience with AI architecture, agentic workflows, and standards like Model Context Protocol (MCP). You’ve thought through tradeoffs, not just followed tutorials.
• Some exposure to local model infrastructure. You’ve run or experimented with local model deployments using something like vLLM, MLX, or similar.
• A sense for enterprise IT. Enough understanding of enterprise infrastructure and data pipelines to reason credibly about where orchestration fits in a customer’s environment.
• Clear communication and composure. You can explain complex ideas simply. You can tell a senior stakeholder “I don’t know yet, but here’s how I’d find out” without losing your footing.

Aren’t sure if you’re a match? We know that impostor syndrome and the confidence gap can prevent us from meeting spectacular candidates — so don’t hesitate to apply; you could be the perfect fit!

Location
US Remote
PST or MST preferred

Compensation and Benefits 

Boomi is committed to fair and equitable compensation practices. Base compensation for this position ranges from $155K - $214K. This position is remote-friendly and, as such, final compensation will be determined by various factors including the candidate’s knowledge, skills, experience, and geographic location. An overview of our benefits can be found here.

#LI-ES1

#Remote