Forward Deployed Engineer

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Thermo Fisher Scientific is seeking a Forward Deployed Engineer / AI Solution Architect to accelerate the design, deployment, and scaling of AI-enabled solutions across the enterprise. This role will operate at the intersection of business strategy, enterprise architecture, AI engineering, and product execution, helping translate high-value business needs into secure, scalable, reusable technical solutions. The ideal candidate brings the hands-on technical depth of a forward deployed engineer, the systems thinking of a solution architect, and the stakeholder fluency required to operate across a large, complex global enterprise. This role will partner closely with business teams, IT, data owners, security, enterprise architecture, platform owners, and AI governance groups to identify use cases, shape solution approaches, build prototypes, guide production delivery, and create repeatable patterns that can scale across Thermo Fisher. This is not a traditional advisory-only architecture role. The person in this role must be comfortable moving from ambiguity to action: understanding workflows, scoping opportunities, building or guiding prototypes, making practical architecture tradeoffs, and ensuring solutions are designed for adoption, maintainability, compliance, and enterprise scale. Location: [... source excerpt omitted ...] er, many high-value use cases require a bridge between business problem definition and technical execution. This role fills that gap by helping teams move from ideas and pilots to production-ready solutions that fit Thermo Fisher’s architecture, data landscape, security requirements, operating model, and long-term technology strategy. The Forward Deployed Engineer / AI Solution Architect will help ensure that AI solutions are not built as isolated one-off experiments, but as scalable, governed, reusable capabilities that create measurable business value. Key Responsibilities: Use Case Discovery and Technical Scoping Partner with AI transformation team, business and functional s [... source excerpt omitted ...] cal ecosystem. Identify when to use existing enterprise platforms, when to extend current capabilities, and when a new pattern or capability is required. Prototyping, Build, and Production Deployment: Lead or directly contribute to rapid prototypes, proof-of-concepts, and minimum viable solutions that demonstrate business value. Work hands-on with AI tools, APIs, automation platforms, enterprise systems, and data sources to validate solution approaches. Partner with engineering and delivery teams to move successful prototypes into production-ready solutions. Guide teams through technical tradeoffs across speed, scalability, cost, reliability, user experience, and governance.