Generative AI Engineer
Capco is hiring a Generative AI Engineer in Milan, Italy. It pays €43k a year and Level rates it ; you can apply on Capco.
Level's read on this job
- Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
- The posting mentions LangChain, LangGraph and RAG among its tools and skills.
- Capco has 702 other open roles on Level.
AI in this role
Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
About Capco
Capco is a global technology and business consultancy, focused on the financial services sector. We are growing at fast pace in our Italian office, the opportunity for growth is large, accessible, and immediate. We are passionate about helping our clients succeed in an ever-changing industry. Capco is going through a significant growth journey, now is a very good time to join us as we expand our consulting team in Italy.
Role Description:
We are looking for a Generative AI Engineer to join the Capco AI Lab and help design and build production-grade AI solutions for our clients.
This is a hands-on engineering role for someone with a strong software engineering background and expertise in Generative and Agentic AI. You will contribute to technical and architectural decisions and, importantly, write and review production code.
You will work on complex AI systems covering LLM orchestration, AI agents, RAG, tool and function calling, evaluation and observability, taking solutions from early prototypes through to scalable production environments.
The role also involves collaborating directly with clients, translating business requirements into robust technical solutions and contributing to discussions on AI architecture, platforms and technology choices.
Responsibilities
- Design and contribute to the end-to-end architecture of Generative and Agentic AI solutions, including orchestration, AI agents, tool/function calling, RAG, memory and state management.
- Remain hands-on with software development, building complex components and taking prototypes through to production-grade solutions.
- Apply engineering standards and best practices for AI applications, including reference architectures, testing and evaluation strategies, guardrails, observability and CI/CD.
- Design scalable, secure and reliable AI systems, considering performance, latency, cost, monitoring and production requirements.
- Evaluate and recommend appropriate LLMs, frameworks, platforms and tools based on technical and business requirements.
- Participate in technical design and code reviews, collaborate with other engineers and contribute to maintaining high engineering standards across the team.
- Work directly with clients and stakeholders to translate business requirements into technical solutions and clearly communicate technical decisions and trade-offs.
- Contribute to technical documentation, reference architectures and knowledge sharing around Generative and Agentic AI.
Skills and Experience
Essential skills to succeed
- Professional experience in Software Engineering/Backend Engineering, including experience designing and building enterprise-grade systems.
- Strong hands-on software engineering skills and experience writing high-quality production code with Python.
- Demonstrable experience designing and developing LLM and Agentic AI applications, including AI agents, LLM orchestration and tool/function calling.
- Strong understanding of RAG architectures, retrieval approaches and vector-based search.
- Experience with agentic frameworks and integration approaches such as LangChain, LangGraph, MCP or comparable technologies.
- Understanding of how to test and evaluate non-deterministic AI systems, including LLM/agent evaluation, monitoring and observability.
- Strong software architecture and engineering fundamentals, including APIs, distributed systems, integration patterns and production reliability.
- Strong experience with at least one major cloud platform (AWS, Azure or GCP) and cloud-native engineering practices.
- Experience with modern software engineering and DevOps practices, including containers and CI/CD. Experience with Infrastructure as Code and observability is highly valued.
- Experience contributing to architecture/design reviews and code reviews, while remaining actively involved in engineering and development.
- Ability to communicate complex technical concepts clearly and confidently to both technical and non-technical stakeholders.
- Solid professional English.
Bonus points
- Experience with multi-agent architectures, advanced RAG, AI evaluation frameworks or LLMOps.
- Experience with NLP and production applications based on Large Language Models.
- Experience taking AI prototypes through to secure, scalable and production-grade applications.
- Experience with AI governance, risk or assurance frameworks, such as the EU AI Act, ISO/IEC 42001 or NIST AI RMF.
- Experience working in Financial Services or Energy.
- Previous consulting or client-facing delivery experience.
- Open-source contributions, technical publications, conference speaking or other contributions to the engineering community.
Why join Capco?
You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.
We offer a competitive, people-first benefits package designed to support every aspect of your life:
- Comprehensive health benefit coverage
- Meal Vouchers
- Welfare allowance
- Access to internal and Tier 1 learning platforms
In Capco you will find:
- A work culture focused on innovation and building lasting value for our clients and employees
- Ongoing learning opportunities to help you acquire new skills or deepen existing expertise
- A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients
- A diverse, inclusive, meritocratic culture
Pay Transparency
Capco is committed to providing fair and equitable compensation to our people. Our compensation policies are designed to allow our people to progress through our defined salary range over time as they progress in their role.
The minimum gross annual base salary for this position is from €43.000. The final offer could be higher to reflect the candidate’s experience, skills, and overall fit for the role. Additionally, this position may also be eligible to receive a discretionary/variable bonus payment.
Location
Piazza Gae Aulenti 1, Milano (Garibaldi FS - Garibaldi M2 M5)
#LI-Hybrid
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How we rate this
Generative AI Engineer at Capco rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $184k
Use the typical AI engineer figure as a reference when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Evaluation, NLP, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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