Forward Deployed AI Engineer

Job Description

We're looking for an AI Solution Architect to partner with us on greenfield client projects.

You'll be the technical and delivery lead on engagements, working peer-to-peer with our Principal. Together, you'll scope the work, design the architecture, and build and deploy MVPs together. To be clear, you're not just designing on a whiteboard–you're a seasoned practitioner who enjoys being hands-on in the codebase, reviewing PRs, unblocking the team, and writing the gnarly bits yourself when needed. You're also the primary technical face to the client: gathering requirements, managing expectations, surfacing tradeoffs, and translating between business needs and engineering reality.

The ideal candidate is the rare engineer who's earned the title of "architect" by being excellent at all three legs of the stool: designing systems, shipping code, and maintaining client relationships. You can run a requirements-gathering call in the morning, sketch the system architecture over lunch, and ship a working prototype at the end of the day. You have a product mindset: you push back on bad ideas, scope MVPs, care more about what the client actually needs than what they asked for, and prioritize business impact over engineering fanciness.

Over time, we want this role to grow into a sales partner—someone who joins us in pre-sales conversations, helps shape proposals, and eventually leads engagements of their own. We're building toward that, and we're looking for someone who's excited about that arc.

This is not a straight engineering role—you're not here to crush tickets handed to you. It's also not a pure engagement manager role—you will absolutely be writing production code. If you're great at one of those and have no experience in the other, this isn't the right fit. If you’re strong in one and have meaningful experience in the other, then let’s talk.

Responsibilities

• Own greenfield client engagements end-to-end: requirements gathering, architecture, delivery, and client relationship
• Partner with the Principal to scope and grow engagements, creating room to bring on specialized ICs.
• Design AI/backend system architectures (LLM pipelines, agents, RAG, integrations, data flows) that are production-ready and operable
• Write production code—you're the most senior engineer in the room until your client engagement requires more engineers, and even after that, you stay hands-on
• Lead specialized ICs as engagements scale, reviewing PRs and setting technical direction
• Run client meetings: gather requirements, communicate progress, surface tradeoffs, manage expectations
• Translate fuzzy business needs into clear technical specs and implementation plans
• Make and own technical decisions—architecture, tooling, prioritization, scoping
• Push back constructively when clients ask for the wrong thing, and propose what they actually need
• Contribute to evolving Beyond Data's delivery playbook based on what works in the field

Requirements

Need-to-have's

• 5+ years of senior engineering experience, with time spent in architect or tech lead roles.
• Proven track record building and shipping production AI-powered systems (LLMs, agents, RAG, evals)
• Strong software development fundamentals: clean code, testing, system design, observability
• Experience designing and operating cloud-deployed services end-to-end
• Demonstrated ability to own a project from requirements through delivery with a happy client at the end
• Great stakeholder communication skills: you can run the room with technical and non-technical stakeholders alike
• Product mindset: you scope MVPs, kill bad ideas, and prioritize ruthlessly
• Strong sense of ownership—you don't wait to be told what to build
• Advanced Python experience
• Comfortable being the most senior engineer in the room and the primary client contact in the same week

Nice-to-have's

• Consulting or agency experience (you've delivered for external clients before)
• Pre-sales experience: scoping proposals, writing SOWs, partnering on sales calls
• Experience with GCP (our primary cloud platform)
• Data engineering exposure (BigQuery, dbt, modern data stack) for engagements that span beyond pure AI Engineering.
• Startup background—you've been close enough to the business to understand commercial tradeoffs
• Experience working in distributed/remote teams