Forward Deployment AI Engineer

Forward Deployed AI Engineer

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.

Position Summary

As a forward deployed AI Engineer, you will serve as an embedded technical expert supporting the development, deployment, and sustainment of AI-enabled solutions across Boston Scientific's global supply chain and sourcing organizations. This role will partner closely with other forward deployed AI engineers, internal product owners, subject matter experts, and end users to co-develop scalable solutions that deliver meaningful business outcomes for a company that builds life-saving medical devices.

The organization will empower its Forward Deployed AI Engineers to address high levels of complexity and own the composition of solutions. The Forward Deployment AI Engineer will be responsible for translating workflow needs into production-ready applications, pipelines, ontology objects, validation logic, and technical documentation. This role will be key in executing against the executive-approved strategic supply chain and sourcing digital roadmap.

Purpose of the Role

Operate as Boston Scientific's forward deployment AI engineer to ensure key global supply chain and sourcing use cases move from requirements gathering through production deployment with clear ownership, technical documentation, validation, and ongoing support.

Key Responsibilities

Solution Development & Technical Execution

• Embed directly with business operators to deeply understand their workflows, constraints, incentives, failure modes, and sources of friction translating ambiguous problems into solvable, high-value technical opportunities across application behavior, data logic, technical specifications, and validation criteria
• Rapidly prototype and iterate solutions using ontologies, AI, and custom engineering building just enough to validate direction, then scaling the proven patterns into robust systems.
• Design end-to-end workflows that connect ontology objects, data integrations, models, and applications into coherent operational solutions that deliver measurable outcomes.
• Deploy bleeding-edge AI capabilities in a regulated industry, and build alongside external forward deployed engineers, technical experts in scaling technologies and AI leaders.
• Diagnose and resolve complex system behaviors across data pipelines, ontologies, applications, and deployment environments, often in real time with frontline business stakeholders.
• Own the technical execution of assigned sourcing and supply chain use cases from requirements gathering through production deployment.
• Build, configure, test, and refine application functionality in partnership with product owners, sourcing SMEs, process leads, and end users.
• Partner with internal data teams and external technical resources focused on the data platform to identify data gaps, pipeline issues, system constraints, and application defects related to data hydration.
• Contribute to reusable patterns, logic, and documentation in lockstep with INFRA teams that can accelerate future sourcing and supply chain use cases.

Business Validation & Stakeholder Partnership

• Serve as the tactical connective tissue between business and engineering, converting operational insights into structured requirements, architecture decisions, and delivery priorities to then build.
• Facilitate clear feedback loops between technical teams and business stakeholders to ensure user needs are accurately reflected in delivered solutions.
• Partner with users to confirm applications reflect real-world processes, decision points, and compliance requirements. Help turn prototype feedback into prioritized technical changes, defects, enhancements, or product decisions.
• Validate application behavior and data logic with SMEs, end users, and product owners.
• Support user acceptance testing, application readiness, production validation, and post-deployment issue resolution.
• Champion operational excellence and velocity, ensuring engineering choices support maintainability, ontology coherence, security guardrails, and sustainable adoption—not one-off heroics or brittle prototypes.

Required Skills & Qualifications

• Working knowledge of, or strong aptitude to learn, market leading data and execution platform capabilities.
• 2 to 4 years of (intense) software engineering experience
• Proven track record as an expert-level individual contributor
• Software engineering background with proficiency in Expertise in TypeScript, Node.js, React, and Next.js or similar packages/languages/frameworks and Python
• Hands-on experience building with LLMs and AI agents in production systems
• Deep understanding of repository architecture and management
• Familiarity with the developer tools ecosystem VSCode extensions, CLIs, and third-party integrations
• Experience translating ambiguous business requirements into technical specifications, application behavior, validation logic, and deployable solutions.
• Strong problem-solving skills and comfort operating in ambiguous, fast-moving project environments.
• Ability to document technical decisions, design logic, assumptions, dependencies, and support requirements clearly.
• Demonstrated ability to partner across technical, business, and external consulting teams.

Preferred Skills & Experience

• Experience working in supply chain, sourcing, procurement, contract management, invoice management, supplier management, or compliance-related workflows.
• Familiarity with enterprise systems such as Ariba, SAP, ERP platforms, data warehouses, or related procurement/supply chain applications.
• Experience supporting production applications, troubleshooting data issues, and validating user-facing application behavior.
• Exposure to ontology design, object-oriented data modeling, workflow automation, or AI-enabled business applications.
• Experience working in agile, sprint-based, or product-oriented delivery environments.
• Ability to communicate technical tradeoffs clearly to business stakeholders and leadership.