Thermo Fisher Scientific · 1 day ago
Senior GenAI/AI Solutions Architect
Alaska, United States
Full-time
Onsite
Senior Level, Lead/Staff
$94K/yr - $141K/yr
7+ years expThermo Fisher Scientific is a company focused on making a positive impact on a global scale. They are seeking a Senior GenAI/AI Solutions Architect to translate business challenges into scalable, secure AI solutions across the PSG value chain, collaborating with various teams to deliver end-to-end implementations from concept to deployment.
BioinformaticsBiotechnologyCloud Data ServicesConsultingHealth CareLife ScienceManagement Information SystemsOffice SuppliesPrecision Medicine
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
Qualification
Required
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
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
Company
Thermo Fisher Scientific
Thermo Fisher Scientific is a biotechnology and laboratory equipment company that provides a wide range of scientific products and services.
10001+ employees
H1B Sponsorship
Thermo Fisher Scientific has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (272)
2024 (224)
2023 (233)
2022 (342)
2021 (315)
2020 (227)
Funding
Current Stage
Public CompanyTotal Funding
$15.97BKey Investors
National Grid
2025-11-24Post Ipo Debt· $2.42B
2025-09-30Post Ipo Debt· $2.5B
2023-08-07Post Ipo Debt· $2.95B
Leadership Team
Stephen Williamson
Senior Vice President and Chief Financial Officer
Daniella Cramp
Senior Vice President and President, Bioproduction Group
Recent News
2026-01-09
Research & Development World
2026-01-09
EIN Presswire
2026-01-07
Company data provided by crunchbase