Senior Tech Lead

We are one of the leading technology groups in Italy, with operations in the United States. We operate as a Business & Technology Accelerator for companies, financial institutions, and public sector organizations, supporting the evolution of their IT and digital strategies. Through an ecosystem of companies that share values, business strategies, and a common vision, we enable our clients to unlock the full potential of technology, amplifying its positive impact on both the economy and society. This role is dedicated to our US market.

What to expect

As our Senior Tech Lead, you lead the core team: the small team that builds and runs the foundations under our products, which serve two markets: analytics, lending and marketing decisions for US credit unions on their own core banking data, and masterdata enrichment for industrial distributors. Each product has its own team building on top, and all of them depend on the core — the platform they run on, the data platforms that feed them, the shared API with search, email and agent services, and the engines that train and score their models—on an open-source stack split by a red line between a private datacenter, where member data stays, and a public cloud. The CTO sets the stack and decides what we adopt, and much of the core is already built, so part of the job is taking over code and decisions made before you arrived and making them your own. Within those calls you make the major architectural decisions for the core—how its code is organized, how services call each other, how security is handled—and make it work. Your team is small and spans platform, data and backend engineering, working with the data scientists: you plan, unblock and review, design how models reach production, write code where the plan needs it, and back up the platform engineer, so the two of you plan your holidays around each other. You do not lead the product teams, but you agree the interfaces with their leads and sometimes work directly with their developers. Credit-union data is regulated (GLBA, FCRA, ECOA), so tenant isolation and auditability are design constraints, not afterthoughts. Our stack is Java/Spring Boot, Python, PostgreSQL, Kubernetes and Dagster, but we hire for the understanding underneath the tool and expect you to carry it across. Your ultimate goal is a core the product teams build on without waiting for you, on a design every engineer can explain.

What you will do

• Team Leadership: Plan the core team’s work, unblock it, and review code and schema changes before they ship, leading from inside the codebase rather than above it.

• Core Architecture & Interfaces: Take over the core as it stands: within the stack the CTO chooses, decide what to keep or change, how the core is organized and how its services call each other, and set the interfaces the product teams build on— API contracts, events, data ownership—so that either side can change without breaking the other.

• Security, Tenancy & Auditability: Design into the core least privilege, every request scoped to the right client, member data on the right side of the red line, and regulated decisions recorded with their inputs, reasons and model version, for a dispute or an examiner.

• MLOps Design: Design how a model reaches production—hand-over format, promotion and rollback, batch or online scoring —for the model repository, then the learning engine, then the inference engine. The data scientists say what each model needs; you set their side of the hand-over and coach them into it, and the platform engineer builds and runs it.

• Hands-On Engineering: Spend the rest of your time in the code where the plan needs it—data pipelines when ingestion peaks, backend features in Java/Spring Boot when the backend overflows—knowing that the split can move.

• Platform Backup: Stand in for the platform engineer during holidays, sickness and incidents, so that the platform never depends on one person.

• Product Teams & Decisions: Agree changes to the core with the product teams’ leads—and with their developers when a change crosses the boundary—write the architecture down as decisions happen, act as the CTO’s sparring partner on architecture and build-versus-adopt, and raise technical risk early.

What we expect from you

• Scope You Have Owned: Experience as a tech lead—or as a senior engineer who held that role in practice—in which you led a team from inside the codebase and owned the design of a production system end to end, living with the consequences after go-live. We weigh what you have owned, not the years it took.

• Hands-On Engineering: You write production code and review others’ with authority, in backend services—Java/Spring Boot preferred; Kotlin or C#/.NET count—and in data pipelines in Python on an orchestrator—Dagster preferred; Airflow or Prefect count.

• Data & Relational Depth: Strong relational modeling and SQL—PostgreSQL preferred; SQL Server, Oracle or MySQL count —from schema design and migrations to the query plan of a slow query.

• Operations in Production: You have run Kubernetes and a relational database in production—PostgreSQL preferred; another you have operated counts—through upgrades, restores and incidents, well enough to stand in for a platform engineer.

• ML in Production: You have put at least one machine learning model into production and kept it running, and you understand validation and leakage well enough to stop a model that is not ready to ship.

• MLOps Design: You can design how a model gets from a data scientist to production—hand-over format, registry, staged promotion and rollback, batch versus online scoring, which model version made each decision—MLflow, Vertex AI, SageMaker or Kubeflow all count.

• Security & Multi-Tenant Design: You treat least privilege, tenant isolation, encryption, audit trails and data residency as design inputs, and can argue row-level versus schema- or database-per-tenant isolation, and a modular monolith versus services.

• Judgment & Communication: You write architecture down so that it outlives the meeting, explain a trade-off to an engineer, a product manager and an auditor, push back on a senior decision—the CTO’s included—with a reason and an alternative, and hold an interface with teams you do not lead.

• Nice to Haves: Leading a core or platform team that other product teams built on; Financial services or credit unions, particularly lending decisions and the record-keeping they require (ECOA/Reg B, FCRA, GLBA); Credit-model governance (approval before go-live, independent validation); Model serving on Kubernetes (KServe or similar) and drift monitoring; Selfmanaged Kubernetes and PostgreSQL operators such as CloudNativePG; Hybrid private-datacenter and public-cloud architectures; Keycloak or another identity provider in depth; LLM features in production and how they are evaluated; SOC 2 or ISO 27001 audits the architecture had to answer.