Drug Product Division (DPD) AI Lead (Remote - EST)
We are looking to hire a candidate with the skills sets mentioned and experience for one of our clients within the pharmaceutical Industry. This is a 6+ month contracting role, with potential for extension. This is a Remote role, with a preference for candidates in the EST zone to facilitate coordination with teams across EST, PST, and EU time zones.
Role Summary:
You are the AI forward-deployed engineer for Drug Product Division (DPD) operations within Thermo Fisher's Pharma Services Group - identifying where AI can improve day-to-day execution, build working solutions, and drive real adoption. You pair DPD operational fluency with hands-on delivery using AWS, Dataiku, Databricks, and OpenAI, and you accelerate ChatGPT adoption across DPD workflows.
This role balances the reality that the business needs value now while enterprise data and AI infrastructure matures over time (for example: MCP server patterns, A2A approaches, reusable agent frameworks, governance, and scalable integrations). You create a vision that aligns quick wins to long-term capability building - and executes against it.
Key Responsibilities:
- Map DPD opportunities for AI: Identify and size use cases across drug product operations (execution insights, investigations support, batch record intelligence, documentation acceleration, knowledge retrieval, exception management, production performance).
- Build and ship solutions: Deliver POCs/MVPs hands-on - integrating GenAI with operational data and controlled documentation in secure, controlled, and adoption-ready ways.
- Roadmap and value cases: Own a DPD AI roadmap with value sizing, dependencies, and adoption plans; align priorities with DPD stakeholders.
- Balance quick wins vs foundations: Build what is needed now while shaping and standardizing patterns that will scale with evolving enterprise data/AI infrastructure (reusable components, integration standards, evaluation/monitoring, agent orchestration patterns).
- Vision and transition plan: Define the DPD AI north star and a staged plan from POCs to reusable capabilities to scaled solutions as infrastructure matures.
- Quality-aware design: Build with regulated realities in mind (traceability expectations, controlled content boundaries, auditability of outputs where required).
- Drive ChatGPT adoption: Create role-based prompt kits, playbooks, SOP-adjacent guidance, and enablement sessions; measure adoption and iterate.
- Stay current and apply responsibly: Continuously monitor the rapidly advancing AI landscape and selectively bring in relevant capabilities that are safe, practical, and measurable in DPD operations.
Required Skills/Qualifications:
- Strong familiarity with DPD operations and how work gets done across a pharma services environment (manufacturing execution, documentation flows, investigations/deviations, quality interfaces, production performance drivers).
- Primary stack: AWS, Dataiku, Databricks, and OpenAI.
- Hands-on technical delivery: Python/SQL plus practical delivery with AWS and Databricks and/or Dataiku, and OpenAI capabilities.
- Applied GenAI experience: prompting, RAG, evaluation, guardrails, workflow integration, and user adoption patterns.
- Strong stakeholder leadership as an IC: discovery workshops, crisp writing, demo-first delivery.
- ChatGPT adoption embedded in DPD routines.
- Demonstrated ability to balance immediate business outcomes with long-term scalable capability building.
- GxP/CSV familiarity and experience designing within controlled-document environments.
- Experience delivering AI solutions across distributed/global operations.
- A DPD-wide opportunity map and prioritized roadmap adopted by DPD leadership.
Other Job Details:
- Job Type: C2C or W2.
- Duration: 6 12 months with high possibility of extension.
- Location: Remote (preferred candidates in the EST zone to facilitate coordination with teams across EST, PST, and EU time zones).
- Pay Rate: $70/hr. on C2C. or $62/hr. on W2.
- Interviews: Video interviews.
- Docs required: ID proof will be required.