Technical Product Owner - AI Coding Platforms

Technical Product Owner – Ai Coding Platforms

At Boston Scientific, we'll give you the opportunity to harness all that's within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we'll help you in advancing your skills and career. Here, you'll be supported in progressing – whatever your ambitions.

Join Boston Scientific at the forefront of innovation as we apply artificial intelligence to accelerate product development, improve engineering productivity, and enable secure, responsible use of AI across the enterprise.

We are seeking a Technical Product Owner – AI Coding Platforms to lead the strategy, roadmap, governance, and adoption of Boston Scientific's AI-enabled software development ecosystem. This role will own the portfolio of AI coding capabilities that support engineers, data scientists, researchers and technical teams in using AI assistants, coding agents, large language model-powered developer tools and workflow automation safely and effectively within enterprise guardrails.

This leader will work across engineering, enterprise platforms, cybersecurity, privacy, legal, procurement and business stakeholders to define and deliver a scalable AI coding platform strategy. The role will also partner closely with external AI vendors and ecosystem partners to shape roadmap priorities, influence feature development and drive enterprise adoption of AI coding capabilities at Boston Scientific.

This role is hybrid at our Marlborough, MA or Maple Grove, MN location, and being in the office for minimum three times a week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time.

Your responsibilities will include:

• Define and own the product vision, strategy and multiquarter roadmap for AI Coding Platforms across the enterprise, aligned with business priorities, engineering needs and responsible AI standards.
• Build and manage a prioritized backlog of platform capabilities supporting use cases such as code generation, code review, test creation, documentation, legacy code modernization, developer knowledge retrieval and workflow automation.
• Partner with engineering, architecture, developer experience, infrastructure and data science teams to integrate AI coding capabilities into integrated development environments, repositories, CI/CD pipelines and internal engineering workflows.
• Lead the evaluation, selection, onboarding and lifecycle management of internal and third-party AI coding tools, models and platforms.
• Serve as the primary product interface with external AI partners, including vendors such as OpenAI, Anthropic and other strategic providers, to manage joint roadmaps, influence feature direction, resolve enterprise adoption barriers and accelerate the rollout of AI coding capabilities at Boston Scientific.
• Drive adoption of AI coding tools through developer engagement, pilot programs, enablement materials, training, office hours, metrics and feedback loops with user communities.
• Establish product requirements and operating standards for security, privacy, compliance, resiliency, auditability and responsible AI use within software development environments.
• Collaborate with cybersecurity, privacy, legal, procurement and risk teams to ensure AI coding solutions meet enterprise and regulatory requirements.
• Define and monitor success metrics for platform performance and business value, including adoption, developer productivity, quality outcomes, policy compliance and cost efficiency.
• Oversee platform operations and governance, including model selection, environment configuration, access controls, usage policies, spend management, rate limiting, telemetry and vendor performance.
• Create standards and guardrails for AI-assisted development practices, including human review expectations, testing requirements, traceability and appropriate use in regulated product and enterprise software environments.
• Translate complex technical capabilities into clear product requirements, user stories, release plans and executive updates for a broad range of stakeholders.

Required qualifications:

• Minimum Bachelor's degree in computer science, engineering, information systems, business or a related field.
• Minimum of 5 years' experience in product management, product ownership, technical program management or platform leadership within a software or technical environment.
• Proven experience owning technical products or platforms used by engineers, developers, data scientists or other technical user groups.
• Hands-on familiarity with AI coding assistants or coding agents such as GitHub Copilot, OpenAI Codex, Claude Code or similar tools used within software development workflows.
• Strong understanding of software development lifecycle practices, Agile delivery methodologies, DevOps, CI/CD, source control and developer tooling ecosystems.
• Experience writing user stories, managing backlogs, prioritizing features and delivering platform capabilities based on business value and user needs.
• Strong knowledge of secure software development practices, privacy and security considerations and governance requirements for enterprise technology platforms.
• Demonstrated ability to evaluate emerging technologies, manage vendors and lead cross-functional decision-making within a matrixed organization.
• Strong analytical, communication and stakeholder management skills with the ability to influence technical and nontechnical audiences.
• Proven ability to lead through ambiguity, balance innovation with risk management and drive measurable adoption of new platform capabilities.

Preferred qualifications:

• Preferred experience in MedTech, health care, life sciences or another highly regulated industry.
• Preferred background in software engineering, solution architecture, developer platforms or enterprise engineering productivity.
• Preferred experience integrating AI capabilities into developer environments, enterprise Git platforms, testing frameworks or software development lifecycle toolchains.
• Familiarity with validation and quality approaches for AI-assisted development in regulated environments.