Forward Deployed Engineer

Excerpt from the original posting

Forward Deployed Engineer 
Building keeps getting cheaper every quarter. What used to take a senior engineer a few weeks now takes an afternoon. The work that does not get cheaper is helping a real business absorb new technology, sequencing the rollout, and knowing when to slow down because something is starting to break under load.
At Heyra, we build operational AI: systems, workflows, and data platforms that live in production from day one. We work with companies that are moving quickly and need solutions that improve the way they operate.
We are looking for a Forward Deployed Engineer. Someone who goes into a client, understands the operation, spots where the real optimisation potential sits, and pushes it all the way through to execution with a strong engineering team behind them.
The role sits between engineering and consulting without fitting cleanly into either. You need to be technical enough to understand data and AI at a deep level. Commercial enough to spot where the business value sits. Patient enough to sit with a manager who is genuinely worried about the tool you just put in front of them. And stubborn enough to stay around once the launch excitement fades and the real adoption work begins.
Most people are strong in one of those. Some in two. Almost nobody walks in with all four. That is exactly the profile we are looking for.

What you will work on
You will embed directly with clients to understand the operation and where the real value sits. You will drive adoption by sequencing rollouts, working with the people who have to use the tool, and staying through the unglamorous part. You will translate business needs into AI solutions that actually ship. And you will learn when to push, when to slow down, and when something is starting to break under load.
You work closely with engineers, data specialists, strategists, and designers in a company where the distance from thinking to building is intentionally small.

Experience with management consulting, change management, or adoption of AI solutions in production. An understanding of software development, ML or data engineering. Familiarity with AI and GenAI frameworks, possibly with some MLOps and evals exposure. Experience with cloud environments like Azure or GCP.
Coding with agents like Claude Code, Codex or Cursor. Working directly with clients and stakeholders. Owning delivery end to end, from a vague problem to a live, adopted solution.
Curiosity, taste and a builder mentality matter just…

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