Engineering Manager - Intelligent Core

We’re looking for an Engineering Manager to lead people, initiatives, and organizational improvement at the intersection of medical AI, product delivery, and engineering excellence.

This is a broad, high-ownership role with three connected scopes.

• First, you’ll lead the people: engineers, QAs,  data scientists, and researchers working on our medical ontology and inference engine - the intellectual and technical backbone of everything we ship.
• Second, you’ll lead the system of delivery. In each cycle, you’ll be responsible for 2–3 cross-functional initiatives. Your role will be to select the right leaders for each, shape the team around the goal, make sure the ambition is clear, and support execution from start to finish. The shape of these teams will change as priorities evolve. That’s intentional.
• Third, you’ll contribute to how Infermedica operates as an engineering organization. You’ll work across teams to identify friction, improve planning and delivery, strengthen AI engineering practices, and evolve processes or roles where needed. The goal is not process for its own sake. The goal is to build an organization that becomes faster, healthier, and more capable over time.

Across all three scopes, you’ll partner closely with Product, Regulatory, and other engineering areas to shape what we build, how we build it, and how we continuously improve. You’ll also act as a connector: bridging teams, aggregating context across workstreams, and making sure the right people are aligned at the right time. At Infermedica, accuracy, safety, and regulatory compliance are not constraints to work around. They are core requirements to design with.

Success in this role means:

• New workstreams spin up quickly, with clear goals, strong ownership, and teams that consistently deliver on ambitious commitments.
• Your people grow - engineers working with you develop into stronger senior ICs, initiative leads, and future engineering leaders.
• Initiative leads in your area operate with high autonomy and agency, making good decisions without constant escalation.
• Engineering delivery becomes smoother and more predictable without compromising safety, quality, or regulatory readiness.
• Regulatory and compliance expectations are embedded into how teams work, so they support good delivery rather than slow it down.

This is a role with real scope and real ambiguity. You’ll succeed if you can combine strong people leadership with hands-on operating discipline - and if others experience you as clear, reliable, demanding in the right way, and easy to work with.

• Lead and develop people - manage engineers, QAs, data scientists, and researchers with care and high standards. Run structured 1:1s, give clear and actionable feedback, support career development, and create conditions where people can do their best work. Invest in growing senior ICs and emerging leads by expanding their scope, judgment, and ability to drive complex technical and product decisions.

• Own initiative delivery - in each cycle, take accountability for 2–3 cross-functional initiatives. Help define clear goals, shape scope, align stakeholders, remove blockers, and drive execution through delivery and learning. You will not be the day-to-day owner of every task, but you are accountable for making sure the work lands and that teams stay aligned across workstreams.

• Spin up teams around changing priorities - assemble the right people from your group and adjacent areas as new workstreams emerge. Create shared context quickly, clarify ownership, establish ways of working, and build momentum - often under tight timelines.

• Coach initiative leads - support others in making good decisions, managing execution, and navigating ambiguity. Step in when needed to unblock or sharpen direction, while helping leads build autonomy rather than dependency.

• Improve how engineering operates - identify and remove friction in how teams plan, deliver, and learn - through better processes, clearer norms, or reshaped roles. The measure is whether teams are faster, healthier, and more capable, not whether a process exists.

• Embed quality, safety, and regulatory thinking into delivery - work with engineering, clinical, product, and regulatory peers to make quality and compliance part of how teams build software, not a gate at the end. Help reduce unnecessary tension between speed and safety by making the right path clear, practical, and repeatable.

• 5+ years of engineering management experience, with strong fundamentals in people leadership, delivery ownership, and technical decision-making.

• Strong people leadership practice: structured 1:1s, meaningful feedback, performance development, and the ability to hold a high bar without burning people out.

• Proven ability to form teams around new or changing priorities: you can quickly create shared context, clarify ownership, establish ways of working, and build momentum under time pressure.

• Experience owning complex initiatives end-to-end: from scoping and team composition through delivery, learning, and follow-through on outcomes. You know how to coach others, unblock execution, and step in when needed without taking ownership away from the team.

• Technical fluency sufficient to earn the trust of senior engineers: you do not need to be the best engineer in the room, but you can engage meaningfully in architecture discussions, spot risks in technical plans, and make informed tradeoffs.

• Demonstrated product and business awareness: you connect engineering decisions to customer value, business priorities, and operational constraints, and you communicate clearly with cross-functional stakeholders.

• Strong collaboration instincts: you naturally act as a connector between teams, surface the right information to the right people, and make cross-functional work easier rather than harder.

• Comfort operating in environments where quality, reliability, safety, or compliance matter, and where good engineering judgment includes understanding risk.

• Fluent in English and Polish, written and spoken, with the ability to communicate clearly across technical, clinical, and business audiences.

• Experience in healthtech, medtech, clinical AI, or another domain where product and engineering decisions can have direct real-world consequences.

• Familiarity with healthcare regulations (MDR/SaMD)

• Background leading teams that include diverse functions, such as engineers, data scientists, ML engineers, or researchers working toward the same product outcome.

• Practical experience applying AI tools in the software development lifecycle, with good judgment about where they genuinely improve engineering effectiveness and where they create more risk than value.

• Experience building, deploying, or operating AI/ML-powered products in production.