Forward-Deployed AI Engineer
Pubblicato il 22-10-2026 - Gemmo in Lombardia
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This is a 6-month paid internship in our AI Lab in Milan.
It is designed to lead to a permanent, full-time role as a Forward-Deployed AI Engineer, so we only offer it to people who can join us full-time as soon as it ends.
It’s for you if you:
- are in the final year of a Bachelor’s degree, or
- are in the final year of a Master’s degree, or
- completed a Bachelor’s degree in the last 12 months, or
- completed a Master’s degree in the last 12 months.
It’s not for you if you:
- are in an earlier year of your degree, or
- plan to continue your studies after the internship
About Us
We are an AI startup founded in 2020, headquartered in Dublin, Ireland, with an AI Lab in Milan, Italy. Our expertise spans Machine Learning and Generative AI for Financial Services.
At Gemmo AI, we build custom AI solutions that combine automation with human insight. We use a modular approach: first we explore the highest-impact opportunities, then we design and deploy tailored solutions, and finally we help improve and maintain them over time.
We believe in responsible, pragmatic AI: systems that integrate into real workflows, provide measurable value, and remain under the client’s control.
Our Team
Forward-Deployed Engineers: 20 people, including 4 Ph.D.s
Leadership: 4 people
We are a lean, technical-first team, and we’re growing.
We plan to add 10 new Forward-Deployed AI Engineers in the next 6 months.
The Role
A forward-deployed engineer works directly with the client and owns the solution end to end: from understanding the business problem, to choosing and building the right model, to shipping and running it in production. There’s no handoff chain.
The same engineer who hears the problem delivers the answer.
In practice, the role combines three disciplines:
Business Analysis: understanding how a financial institution works, mapping its processes, and turning a vague request into a clear specification.
AI Engineering: building, evaluating and improving models, from classic prediction models to fine-tuned LLMs, and AI Ops.
Software Engineering: building the APIs, integrations and applications that put models into real workflows, then deploying and maintaining them.
Nobody arrives strong in all three. We hire people who are solid in at least one and eager to grow into the others.
Who You Are
- You enjoy understanding why something needs to be built, and you take ownership of outcomes the client can measure, not just tasks
- You’re comfortable working directly with clients and resolving unclear problems with them, rather than waiting for a perfect spec
- You’re curious across business, AI and software, especially about how financial services companies operate and make money
- You write clearly and communicate confidently in English, both written and spoken: we work in English with international clients and colleagues. Italian is a plus, not a requirement
- Prior work experience is not required: we welcome students and graduates from ITS,
bachelor’s and master’s programmes. What matters most is how fast you learn
What You’ll Do
You’ll be embedded with enterprise clients in regulated financial services, one of the most data-rich industries in the world, and own AI solutions from the business problem to production. Depending on the project, you might:
- Sit with client stakeholders to understand a workflow, identify where AI creates measurable value and redesign the process around it
- Build prediction models, ML-based document analysis and retrieval (RAG) pipelines that power conversational interfaces over the client’s data
- Evaluate, benchmark and orchestrate open-weight models and agents
- Build the full-stack applications, APIs and integrations that connect your models to users and to the client’s systems
- Deploy, monitor and improve what you’ve built once it’s live
You’ll join an operating team of FD AI Engineers and AI Leads, with a dedicated mentor at your side. There are no handoffs to other teams: you own the outcome, and you’ll use AI tools every day to multiply what you deliver. This is not a support role: you’ll be expected to contribute from day one.
What You Will Learn
- Turning a vague client request into a clear spec, then into a working version
- Building, evaluating and orchestrating ML and LLM-based systems: retrieval, evals and agents
- Building full-stack applications and APIs that serve models to real users, and running them in production on Azure and Snowflake
- Communicating technical work clearly to non-technical stakeholders
- How a business operates and makes money, and what it takes to build AI in a regulated i