Job Description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

As part of the Thermo Fisher Scientific team, you'll 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 world's 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 Fisher's 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

The salary range estimated for this position based in Canada is $94,100.00-$141,125.00.