Senior Product Engineer, AI

• Way of working: hybrid, office in Turin (city centre), around 8 days per month on site, managed flexibly

  
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• Key tech skills: Python and/or TypeScript, system design, GCP, IaC, LLM engineering (RAG, agents, evaluation), data warehouses

• Experience: at least 8 years as a software, backend or product engineer, with product experience

• Gross annual salary: €70,000 - €75,000 + welfare

Welyk is recruiting on behalf of Digital Pills, a consulting company focused exclusively on data, based in Turin with around 30 people. The company covers the entire data value chain: data strategy, data engineering, analytics engineering, BI and data science, and over the last two years it has significantly strengthened its AI practice. It works with large international clients (including HelloFresh, Airalo and Last Minute) and Italian enterprise brands, and is pursuing an international expansion. It also dedicates a significant part of its activity to the non-profit sector, including pro bono projects for organisations such as AIRC and Save the Children.

Digital Pills recently received an investment from RIF-T, a vehicle controlled by Equiter and funded by Fondazione Compagnia di San Paolo, to support its scale‑up phase. With this investment the company is moving from a 100% consulting model, where every project is built from scratch, to a scalable model based on proprietary products and accelerators: reusable components across different clients that reduce project variability and enable new sales models, such as pay per use. Part of this work already exists (for example, a proprietary framework for data integration projects). This position was created to lead the transition full time: it is a role entirely dedicated to R&D and productization, not staffed on client projects.

• Build products and accelerators yourself, from architecture to deployment and maintenance, taking an idea to a first working version even without a development team

• Review the projects the company sells and starts, together with the CTO and the tech leaders, to understand what is already reusable, which new assets could emerge and what limits their replicability

• Define and drive the roadmap of products and accelerators, deciding with the CTO what to build and what not to build, based on replicability and a simple business case (delivery time saved, margin, number of projects it applies to)

• Integrate generative AI and LLMs into production applications, going beyond the demo towards reliable, observable and maintainable systems

• Own the cloud and infrastructure of the products you build (GCP or equivalent, CI/CD, IaC, observability, security) and set their engineering practices

• Support the CTO and client managers in pre-sales with architectures, estimates and an assessment of the replicability potential, contributing to the shift from selling days to value-based and pay-per-use models

• Once a product is mature enough, hand it over to a dedicated team and move on to the next one

• At least 8 years of experience as a software, backend or product engineer, with real ownership of production systems

• Product experience: you have built products, accelerators or internal tools that were actually adopted, and you contributed to deciding what to build, not only to building it

• Python and/or TypeScript/JavaScript at a senior level, API design and backend development (REST, event-driven architectures), authentication and authorization, asynchronous jobs and queues

• Relational and document databases, advanced SQL, data warehouses (BigQuery, Snowflake, Redshift or similar), ETL/ELT concepts

• Cloud (GCP preferred, AWS or Azure are fine), Docker, CI/CD (GitHub Actions, GitLab CI, Cloud Build), Infrastructure as Code (Terraform, Pulumi)

• LLM engineering: LLM APIs and prompt engineering, RAG, vector stores, agentic workflows, evaluation and observability of LLM systems, agent protocols (MCP or similar)

• Fluent Italian and C1 English

• Experience in consulting or professional services, or familiarity with its dynamics: project scope, estimates, days, budgets, margins

• Product management or productization experience

• Familiarity with the marketing and customer data stack (behavioural data, CDPs, ad platform data) and with customer-journey data modelling for acquisition and retention

• Experience with international stakeholders and availability for occasional trips to Berlin (roughly one week per quarter)