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About the Role

Thermo Fisher's PPD clinical research group (CRG) is leveraging digital innovation, data science, and AI to accelerate the delivery of life-changing therapies to patients. This role is responsible for building, operating, and scaling CRG Digital’s end-to-end AI engineering and platform capability, ensuring AI-enabled solutions are production-ready, scalable, and integrated into business operations.

Responsibilities

• Lead product-aligned engineering teams to deliver AI-enabled applications and services at scale, with a strong emphasis on AI-native development practices.
• Redefine engineering productivity by driving adoption of AI-assisted and agent-based development, including AI coding assistants, agent-enabled code generation, testing, refactoring, and automated documentation and code review workflows.
• Establish a target operating model where individual engineers are significantly amplified by AI tooling, enabling 1 engineer to deliver the output of multiple traditional engineers through effective human–AI collaboration.
• Shift engineering focus from manual coding to solution architecture and system design, validation, testing, and quality assurance of AI-generated code and integration of AI services into scalable systems.
• Own the reliable, high-quality delivery of AI/ML and GenAI solutions, AI-enabled product features and APIs, and integrated data and feature pipelines.
• Establish a high-throughput engineering model driven by rapid iteration cycles, automation-first development workflows, and reuse of components and services.
• Partner with Solution Architecture to translate use cases into scalable, production-ready solutions, ensuring alignment between design intent and engineering execution.
• Ensure seamless integration of AI capabilities into digital products and workflows, with a focus on speed, adaptability, and maintainability.
• Build and scale a modern AI-native execution layer that operationalizes AI-driven decisions into real-world actions.
• Integrate and evolve capabilities including APIs and system integrations, workflow orchestration frameworks, and intelligent automation (including RPA as a supporting capability).
• Ensure automation is AI-driven, not task-driven, reusable, and standardized, tightly integrated with platform and AI services.
• Enable execution patterns that support human-in-the-loop, semi-autonomous, and agentic workflows.
• Establish and scale end-to-end AI lifecycle management, including model development, validation, deployment, monitoring, versioning, performance tracking, and drift detection.
• Ensure platform and engineering systems meet requirements for reliability, scalability, cost efficiency, observability, and monitoring.
• Embed governance-by-design in partnership with AI Risk & Compliance, including auditability, traceability, and secure and compliant development practices.
• Define and manage the ecosystem of engineering and platform partners.
• Drive effective onshore/offshore and partner delivery models aligned to group needs.
• Ensure partners contribute to reusable assets and platform capabilities and speed and quality of delivery.
• Lead internal capability building in AI engineering, platform engineering, and emerging AI and agentic technologies.
• Build and lead a high-performing organization across AI engineering, platform engineering, and automation and orchestration capabilities.
• Define roles, skill models, and career paths aligned to future-state AI capabilities.
• Foster a culture of engineering excellence, innovation, reuse, accountability, and continuous improvement.

Requirements

• Bachelor’s degree required; advanced degree preferred (computer science, engineering, AI/ML, or related field).
• 12 years of experience in software engineering, platform engineering, or technology leadership roles, with a proven track record of building and scaling high-performing engineering organizations.
• Demonstrated experience defining and implementing scalable, reusable platform architectures and shared capability layers in complex enterprise environments.
• Experience delivering AI/ML and/or GenAI-enabled systems in production, including understanding of model lifecycle, integration patterns, and operational considerations.
• Proven ability to evolve engineering organizations toward modern, automation-first and AI-assisted development practices, driving meaningful improvements in speed, quality, and efficiency.
• Demonstrated success driving step-change improvements in engineering productivity and delivery models, including adoption of AI-assisted or agent-based development approaches.
• Experience operating in complex, matrixed organizations with cross-functional stakeholders across Product, Data, AI, and Business teams.
• Experience in regulated environments (e.g., healthcare, life sciences) preferred, with an understanding of compliance, security, and quality considerations in engineering systems.
• Able to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner.
• Able to work upright and stationary for typical working hours.
• Ability to use and learn standard office equipment and technology with proficiency.
• Able to perform successfully under pressure while prioritizing and handling multiple projects or activities.
• Must be legally authorized to work in the United States without sponsorship.
• Must be able to pass a comprehensive background check, which includes a drug screening.

Skills

• Strong systems thinking with the ability to design scalable, reusable architecture patterns rather than point solutions.
• Deep technical and strategic understanding of AI engineering, platform architecture, and modern software systems, with the ability to translate these into business and operational impact.
• Ability to operate effectively at both deep technical and executive levels, bridging architecture, engineering execution, and business priorities.
• Strong orientation toward automation, reuse, and platform leverage over bespoke development approaches.
• Demonstrated ability to lead transformation of engineering practices, including adoption of AI-assisted and agent-enabled development models.
• Strong leadership and organizational design capability, with experience building and scaling multidisciplinary engineering and platform teams.
• Excellent stakeholder management and communication skills, with the ability to influence across Product, Data, AI, Risk, and Business functions.
• Ability to balance speed, quality, cost efficiency, and regulatory compliance in a complex and evolving environment.
• Comfortable operating in ambiguity and leading teams through rapidly evolving technology landscapes, including emerging AI and agentic capabilities.
• AI-assisted development
• Agent-based development
• AI coding assistants
• AI-native development practices
• MLOps
• Lifecycle management
• Automation
• Orchestration
• RPA
• APIs
• System integrations
• Workflow orchestration frameworks
• Model development
• Model validation
• Model deployment
• Model monitoring
• Versioning
• Performance tracking
• Drift detection
• Reliability
• Scalability
• Cost efficiency
• Observability
• Governance
• Auditability
• Traceability
• Secure development practices
• Compliant development practices

Location

• Remote US (east coast preference)

Work Type

• Office
• Remote

Experience Level

• Senior leadership
• Band 9 level

Education Level

• Bachelor's degree
• Advanced degree preferred

Salary/Compensations

• $167,500.00–$278,000.00
• Variable annual bonus based on company, team, and/or individual performance results

Benefits

• A choice of national medical and dental plans, and a national vision plan, including health incentive programs
• Employee assistance and family support programs, including commuter benefits and tuition reimbursement
• At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
• Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount

About the Company

• At Thermo Fisher Scientific, we are committed to fostering a healthy and harmonious workplace for our employees. We understand the importance of creating an environment that allows individuals to excel.