Build AI-powered solutions using large language models, retrieval-augmented generation (RAG), agents, tool calling, copilots, automation, and intelligent document and email processing.
Explore emerging technologies—from AI and agents to automation, digital twins and quantum—and run time-boxed experiments, proofs of concept and technology comparisons to separate capability from hype.
Shape technical direction for your prototypes: define architecture, break down delivery, assess existing Stryker capabilities for reuse and make evidence-based build-or-kill decisions, recognising a well-reasoned no as a successful outcome.
Accelerate the Lab’s engineering foundations with reusable starter kits, components, templates, CI/CD pipelines and sandbox patterns, while maintaining clean code, targeted testing, secure defaults and practical documentation.
Stay hands-on while reviewing code, pairing with and mentoring engineers, and partnering with the Lab leader to shape technical direction.
Partner with business stakeholders and Business Innovation Partners to translate problems into buildable scope, clear hypotheses and measurable success criteria.
Turn experimentation into shared insight through concise write-ups, demos, contributions to the Lab’s quarterly innovation radar for ED&T leadership and your own experiment ideas; capture what worked, what did not, and the cost and effort to scale.
Equip delivery teams to scale validated prototypes with a complete handoff covering architecture, data, security context and next steps, working within Enterprise Architecture, cybersecurity, data privacy and QMS guardrails from day one.
What you need
Bachelor’s degree in Computer Science, Software Engineering or a related field, with 5–8 years of professional software engineering experience in delivering full-stack web applications end to end. A relevant master’s degree is a plus.
Strong front-end expertise in React and TypeScript, or a comparable modern framework such as Angular, combined with back-end development in .NET/C#, Node.js or Python, RESTful APIs, and SQL and NoSQL data modelling.
Hands-on cloud-native development and deployment experience, preferably with Microsoft Azure App Service, Functions, containers, storage and identity. Azure certifications and enterprise integration experience with Microsoft 365, Microsoft Graph, SAP, Power Platform and Microsoft Entra ID single sign-on are advantages.
Practical experience building LLM-powered applications, including RAG, agents or copilots, using Azure OpenAI, OpenAI APIs or similar technologies. Experience with Semantic Kernel, LangChain, LangGraph and Model Context Protocol (MCP) is a plus.
A proven ability to turn concepts into working demos in days or weeks. Experience in an innovation lab, R&D group, startup, rapid product team or software-product company, alongside sustained impact and multi-year ownership across roles, will help you stand out.
Solid engineering foundations in Git, CI/CD, automated testing, Docker and secure coding, with effective daily use of AI coding tools such as GitHub Copilot and sound judgement on code review and quality.
Excellent written and spoken English, with the ability to explain technical trade-offs to non-technical partners and deliver confident demos. Ability to collaborate with a US-based team, including regular US Eastern Time overlap for demos, stand-ups and partner sessions.
Preferred strengths include curiosity demonstrated through open-source contributions, side projects, hackathon wins, technical writing or talks; exposure to computer vision, speech, IoT and edge, digital twins, AR/VR or quantum computing; and experience in healthcare, medical devices or other regulated industries.
Travel Percentage: None
