Engineering Manager

✅ Must-haves

• Technically credible dev-to-manager path, with 5+ years as a strong senior engineer on distributed systems, microservices, and SaaS platforms before leading.
• 4+ years managing after a senior IC run.
• Multi-team management, proven: has led two or more teams concurrently, roughly 10-20 engineers, or managed through tech leads.
• Empower and mentor senior technical leaders, fueling their motivation and career growth by maximizing their autonomy and strategic participation.
• Built teams, not inherited them: sourcing, hiring, developing, and managing out, the full cycle, more than once.
• Experience in regulated or audited delivery environments, such as health, fintech, or government.
• Comfortable shipping against a hard release gate with audit trails.
• Still reads code, challenges designs, and can personally judge whether AI-generated code meets the bar.
• Strong delivery ownership, including stepping in when delivery is at risk and owning squad outcomes, including failures.
• Direct communication style, with the ability to communicate risk early as options and trade-offs.
• Curiosity about the why, including users, the clinical problem, and the outcome before process.
• AI-native openness, with visible eagerness to lead AI-assisted delivery where humans frame and verify, and agents generate.

✨ Nice-to-Haves

• AI-first delivery track record: led teams shipping AI-generated code as the default, with human-in-the-loop review discipline.
• Multi-tenant SaaS architecture experience, including microservices, tenant isolation, RBAC and entitlements, and secure API design.
• Cloud-native operational literacy, including Kubernetes, CI/CD and GitOps, observability, metrics, logs, and tracing.
• Experience scaling an engineering organization through the 15-to-50 stage inside compressed timelines.
• Experience with LLM or agentic features running in production.
• Stack familiarity with.NET, Node.js, React, Python, and Kubernetes.
• Life sciences or clinical trials background.

• A dynamic work environment with an international team, where collaboration and diversity thrive.
• Work alongside top talent, united by a shared purpose and committed to making a real impact.
• Comprehensive private health coverage to ensure your physical and mental well-being.
• Hybrid work model offering flexibility to balance your professional and personal life.
• Company events to celebrate achievements and enjoy time together.
• Get equipped with a MacBook to enhance your productivity and work experience.
• Our office is pet-friendly! You'll likely be greeted by a few wagging tails upon arrival.

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Following our successful expansion into the U.S. and continued growth across Europe, we are seeking an Engineering Manager, SaaS, to help drive our Engineering function from our Austin hub.

Reporting directly to our Head of Engineering, this person will play a critical role in leading delivery health, people development, and hiring across a group of engineering squads.

The delivery mission is to industrialize AI-accelerated prototypes, already validated for product and scientific accuracy, into production-grade, enterprise-deployable systems without losing the speed that built them. This person will keep the AI-native delivery loop honest: intent framed sharply, agent-generated work verified before it scales, and accountability always human.

• Lead 5-8 engineers across one or two squads, with the ability to grow the group to 12-15 engineers across two or three squads through hiring.
• Own delivery health, including lead time, change-failure rate, and a release rhythm the business can trust.
• Ensure timelines are treated as a budget, not a target to negotiate, with scope reprioritized openly when delivery is at risk.
• Maintain AI governance standards, ensuring every AI-generated or AI-modified change is human-reviewed before merge.
• Partner with the AI Research team on model-quality workstreams with enough AI/ML fluency for a real technical dialogue.
• Partner with Product on a single shared scoreboard for outcomes, scope, and delivery priorities.
• Shield squads as the central point of contact, protecting team focus while priorities shift across the portfolio.
• Support a structure where architecture stays with principal engineers, scope and acceptance with Product, and the release gate with the Scientific org.
• Develop engineers and tech leads through coaching, feedback, performance management, and career growth.
• Lead hiring for the group, including sourcing, interviewing, closing offers, and building strong team foundations.

We are looking for an Engineering Manager who multiplies the system rather than routes decisions through themselves.

Someone who has led multiple teams, built teams through hiring and development, and created delivery cultures that can operate in regulated or audited environments. This person should be able to own squad outcomes, protect team focus, partner closely with Product and AI Research, and ensure delivery happens with speed, quality, and strong human governance over AI-assisted work.