Map the client's process
Together with the business owner. You find where an AI agent or workflow really moves the needle. Without tech infatuations.
Open roleHUMAN FACTORS TECHNOLOGY
AI Solution Engineer.
An engineer who goes on-site, understands the process, and builds the AI solution that transforms it. Not just prototypes: software that goes to production and that the client keeps using after we leave.
01 /Who we're looking for
The problem, the process, the solution. In that order.
Go on-site. Understand the process. Build what stays.
We're looking for an engineer with experience in AI projects that went to production. Not on the first try. Someone who's seen what it means to take an agent from a notebook to a system the client keeps using every day.
AI co-delivery isn't desk work and Zoom. It's understanding the client's domain, mapping the process with the business owner, and finding where AI actually moves the needle. Then making it work amid CRMs, ERPs, legacy DBs. Without drama.
02 /What you'll do
Five things, every week.
Build agents that integrate
Real systems: CRM, ERP, ticketing, DMS, legacy DBs. No sandbox: reality is complex enough.
Evaluation pipelines
Measure if the AI does what it should, before going to production. You don't trust a model on its word.
Co-delivery on big projects
You work with senior Hestro consultants on complex projects, autonomously on small ones. Never isolated, never parachuted.
Pass the ball, no drama
You document what's needed, pair with the client's IT team at key release moments. The code stays theirs.
03 /Expected stack
Solid, real, in production.
Required
- Solid production Python (3+ years, not just notebooks)
- LLM APIs (Anthropic, OpenAI, open models via Ollama or vLLM)
- Agent frameworks: at least one of LangGraph, CrewAI, Pydantic-AI, or in-house code
- Integrations: REST APIs, webhooks, event queues, at least one ERP or CRM seriously touched
- Cloud: AWS or Azure
Bonus
- TypeScript for companion UIs
- Docker and container orchestration
- Experience with RAG on 'messy' enterprise data (documents, PDFs, emails)
More than your CV, we care what you've actually shipped to production. Repo, link, demo, whatever: bring it.
04 /Required mindset
Five ways of working, no compromises.
On-site, not just Zoom
Understanding a process happens on-site. Calls are useful, but you see the real workflow by observing in the company.
Explain without condescension
You can talk AI to non-technical people while respecting their intelligence. Never from above.
30% code, 70% understanding
You know the hard part isn't writing the agent. It's understanding what the client truly needs, before writing it.
Start from the problem
Don't fall in love with technology. The fancy model means nothing if it solves the wrong problem.
Not protective of your code
What you build goes to the client or to a colleague without drama. You document, you pair, you pass the ball.
05 /How we work
Time, autonomy, contract form. Seriously.
Short week
The Hestro working time is 4 days out of 7. It's not a pilot, it's the standard.
4/7Remote-first Italy
You decide where to work from. Travel 1-2 days a week to clients.
Flexible contract
Employee, consultancy, ongoing VAT, hybrid. We pick together.
Side projects welcome
Parallel activities (advisory, teaching, open source) are an asset.
06 /How we select
Three steps, collegial decision.
Intro call
With one of the Hestro seniors. We want to know where you come from and what excites you today.
Technical session
For the AI Solution Engineer it's a design conversation on a real integration. Real case, anonymised.
Shadowing day
Stay with us on a live project. Understand if you recognise yourself in how we work.
HUMAN FACTORS TECHNOLOGY
Ready to apply as AI Solution Engineer?
Go to the contact form on the Careers page. Tell us 'AI Solution Engineer' in your message, attach your CV or link your professional profile, and tell us in two lines what you're building right now.
Reply within 5 business days