Director, Team Lead, Software Engineering for Computational Pathology (/f/d)
About AstraZeneca
AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies.
Site Description - Munich, Germany
Welcome to Computational Pathology Munich, one of over 400 sites here at AstraZeneca, providing a collaborative environment where everyone can feel comfortable to be themselves - a value that is at the core of AstraZeneca's priorities. To help you maintain your best self, here's a sneak peek into some of the things we provide: after-work events, lunch & learns, a spacious and sustainable office working environment, events, family and childcare support and of course the Alps around the corner for hiking, biking and skiing.
Position Summary
The Director of Software Engineering for Computational Pathology leads the software engineering capability that develops, deploys, and maintains AI-enabled computational pathology systems for processing and interpreting large-scale digital pathology images for clinical and research use. This leader is accountable for building and scaling high-performing engineering teams, establishing robust software practices, and partnering across multiple functions to deliver compliant, reliable, and impactful computational pathology solutions.
As an emerging leader in the AstraZeneca community, you will lead a core software engineering capability, ensure delivery of team objectives in line with business objectives, and contribute to functional scientific strategy. You will own performance development for your team while demonstrating leadership through project teams, internal consulting, and mentoring.
Key Responsibilities
- Lead a core software engineering capability or team of software engineers working in computational pathology to deliver objectives in line with business objectives and project priorities.
- Collaborate with Quality, Regulatory, and Clinical Affairs to meet SaMD, AI/ML governance, data privacy, and security standards; enforce documentation rigor and audit readiness; align with GxP and ISO 13485; support preparation of validation and regulatory documentation; proactively identify and address critical compliance risks.
- Develops scalable and audit ready solutions for computational pathology based on resilient architectures for AI-based image analysis, data pipelines, model serving, and workflow orchestration. Supports technical decisions, patterns, and platform investments.
- Establish best-in-class SDLC practices, including CI/CD, testing strategies, observability, incident response, change management, and cost optimization across cloud environments. Drive reliability, maintainability, and performance at scale.
- Contributes to functional scientific strategy to enable robust data pipelines, model training/validation workflows, and reproducible MLOps for pathology algorithms. Supports performance, fairness, and generalizability standards for AI in clinical contexts.
- Serve as technical interface with external partners for clinical validation and deployment; drive cross-functional collaborations; build alliances with technology partners and vendors; resolve conflicts and build effective relationships; communicate technical concepts to diverse audiences; conduct briefings and technical meetings.
- Identify and mitigate technical, operational, and security risks. Ensure adherence to cybersecurity, privacy, and data governance policies across platforms and workflows.
- Drive adoption of modern engineering practices and tools; lead organizational change initiatives that improve velocity, quality, and collaboration.
- Lead publications and conference contributions; present at internal and external meetings; participate in professional communities; build ties with centers of excellence; develop recognition as an expert in AI-enabled medical software; contribute to broader scientific discourse.
Qualifications
Required
- Expertise in regulated software development for medical applications with a strong focus in data workflows, deep learning models training, and performance evaluation for machine vision algorithms applied to medical data.
- At least 7 years of experience in the field of software development with at least 2 years of proven experience leading teams functionally or as a line manager. Expertise in AI systems or medical devices validation is a strong asset.
- Domain knowledge in Software as a Medical Device (SaMD), AI systems validation, or medical device development is a must.
- Prior and proven experience of working with standards and frameworks such as IEC 62304, ISO 13485, and ISO 14971 is a must.
- Strong programming skills (python, R, Rust, etc.). Knowledge of at least one of the most common deep learning development frameworks (Pytorch, tensorflow, etc.), data analytics libraries (pandas, R), and the typical software development technology stack (git, JIRA, IDEs, etc.).
- Expertise in scientific studies design, planification, running including experiments planification, execution and reporting.
- Knowledge in data analysis and statistics, in particular applied to data distribution, imbalance and quality assessment for medical applications.
- Knowledge of AI system and medical devices validation including in the fields of stability, explainability, sub-group performance evaluation (e.g., by target population demographics or heterogeneous data distributions like scanner variability).
- Ability to interact with scientists of different background including physicians, biologists, statisticians and computer scientists.
- Excellent written and oral communication skills in English.
Preferred
- Experience supporting verification and validation activities in regulated software development.
- Familiarity with AI/ML-enabled software systems and their development considerations in regulated contexts.
- Knowledge of digital pathology workflows, image formats, and computational pathology applications.
- Experience mentoring junior engineers or supervising technical work.
- Experience contributing to internal or external technical presentations, publications, or engineering knowledge-sharing activities.
What you can expect:
- Individual development opportunities with a focus on lifelong learning
- Trust, appreciation, and room to shape things in a focused and passionate team
- Modern office space in Munich enabling collaborative, flexible, and agile work
- A diverse, inclusive, and bias-free work environment, actively welcoming applications from all qualified candidates, regardless of background or characteristics
Date Posted
17-Aug.-2026
Closing Date
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
