Senior GenAIAI Solutions Architect

Work Schedule

Environmental Conditions

Job Description

As part of the Thermo Fisher Scientific team youll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the worlds toughest challenges like protecting the environment making sure our food is safe or helping find cures for cancer.

DESCRIPTION:

We are seeking a Senior/Lead GenAI/AI Solution Architect to translate business challenges into scalable secure enterprise-grade AI solutions across the PSG value chain (Commercial Operations Finance/Legal Manufacturing Quality Supply Chain). This role sits within IT / Enterprise Architecture and partners with PSG business teams Engineering Data/Platform Security and Quality/Validation to take problems from concept POC prototype validation enterprise deployment operating within GxP expectations where applicable.

KEY RESPONSIBILITIES:

• Business to Solution Delivery: Partner with stakeholders to define problem statements success metrics and solution concepts; deliver end-to-end implementations from POC to scaled enterprise deployment (security governance reliability cost).

• GenAI / Agentic Architecture: Design and build advanced GenAI applications including RAG agentic RAG and multi-agent orchestration integrating into existing enterprise systems and workflows.

• Hands-on Prototyping & Implementation: Build working solutions from the ground up in Python (services/APIs integrations testing and telemetry) to demonstrate value quickly; iterate with users to validate usability and outcomes then harden for production.

• Enterprise Agent Tooling & Standards: Establish reusable patterns reference architectures and organizational standards for agentic systems (e.g. internal enablement artifacts such as skills/standards documentation and agent/tooling foundations).

• LLM Evaluation & Quality Gates: Implement evaluation frameworks (automated human-in-the-loop) for retrieval quality groundedness accuracy safety latency and cost; set up regression testing for prompts and workflows.

• Prompt & Context Engineering: Own best practices for prompt and context engineering (tool schemas prompt/version management context construction retrieval tuning and guardrails).

• Agent Interoperability Patterns: Implement agent interoperability patterns (e.g. Model Context Protocol (MCP) and agent-to-agent messaging patterns) in enterprise contexts (message contracts routing auditability and boundaries).

• Platform & Integration: Work across AWS OpenAI services Databricks Dataiku and SQL ecosystems to enable data access orchestration deployment and monitoring.

• GxP/Validation Partnership (as applicable): Partner with Quality/Validation and Security to support required documentation controls and traceability for regulated or quality-critical deployments.
  

MINIMUM QUALIFICATIONS:

• 7 years in solution architecture and/or senior engineering roles delivering enterprise systems.

• 2 years of experience delivering Generative AI solutions in an enterprise environment including taking solutions from prototype to production-scale deployment.

• Demonstrated ability to take a business problem through solution concept POC prototype validation enterprise scale.

• Demonstrated product and outcome orientation with the ability to prioritize work based on measurable business impact and end-user value.

• Strong hands-on Python experience delivering GenAI systems in an enterprise environment (building services/APIs integrations tests and telemetry).

• Practical experience with LangChain LangGraph and LangSmith (tracing debugging evaluation and/or prompt/workflow regression).

• Experience implementing LLM evaluation frameworks and measurable quality gates for RAG/agentic workflows (automated testing human review loops).

• Experience operationalizing GenAI solutions with monitoring/telemetry prompt/version management and evaluation-driven iteration.

• Experience working in Agile delivery environments (e.g. Scrum/Kanban) collaborating effectively with cross-functional teams through iterative development.

• Proven ability to define quantify and communicate value (e.g. efficiency gains risk reduction cost savings cycle-time improvement) and translate outcomes into success metrics and adoption measures.
  

PREFERRED QUALIFICATIONS:

• Experience with multi-agent systems and enterprise tool execution patterns (governed tools permissions audit trails).

• Experience designing/operating LLMOps/MLOps foundations (versioning monitoring incident/rollback model/prompt governance).

• Experience with enterprise integration patterns (APIs IAM/security logging/audit reliability) and operating in regulated/quality-critical environments (GxP exposure preferred).

• Experience delivering solutions in one or more PSG domains (Commercial Ops Finance/Legal Manufacturing Quality Supply Chain).

• Certifications or deep working knowledge in AWS Databricks and/or Dataiku.
  

Thermo Fisher Values

Demonstrates Thermo Fishers values: Integrity Intensity Innovation and Involvement.

Equal Opportunity Employer

Thermo Fisher Scientific is proud to be an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable laws.

Compensation