Work ScheduleStandard (Mon-Fri)Environmental ConditionsOfficeJob DescriptionAs 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 secure or helping find cures for cancer.DESCRIPTION:We are seeking aSenior/Lead GenAI/AI Solution Architectto translate business challenges into scalable, secure, enterprise-grade AI solutions across thePSG value chain(Commercial Operations, Finance/Legal, Manufacturing, Quality, Supply Chain). This role sits withinIT / Enterprise Architectureand partners with PSG business teams, Engineering, Data/Platform, Security, and Quality/Validation to take problems fromconcept → POC → prototype validation → enterprise deployment, operating withinGxP expectationswhere applicable.KEY RESPONSIBILITIES:Business to Solution Delivery:Partner with stakeholders to define problem statements, success metrics, and solution concepts; deliver end-to-end implementations fromPOC to scaled enterprise deployment(security, governance, reliability, cost).GenAI / Agentic Architecture:Design and build advanced GenAI applications includingRAG, agentic RAG, and multi-agent orchestration, integrating into existing enterprise systems and workflows.Hands-on Prototyping & Implementation:Build working solutions from the ground up inPython(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 regressiontesting 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)andagent-to-agent messaging patterns) in enterprise contexts (message contracts, routing, auditability, and boundaries).Platform & Integration:Work acrossAWS, OpenAI services,Databricks,Dataiku, andSQLecosystems 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 throughsolution 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‑onPythonexperience delivering GenAI systems in an enterprise environment (building services/APIs, integrations, tests, and telemetry).Practical experience withLangChain, LangGraph, and LangSmith(tracing, debugging,



evaluation, and/or prompt/workflow regression).Experience implementingLLM evaluation frameworksand measurable quality gates forRAG/agentic workflows(automated testing + human review loops).Experience operationalizing GenAI solutions withmonitoring/telemetry, prompt/version management, and evaluation-driven iteration.Experience working inAgile delivery environments(e.G., Scrum/Kanban), collaborating effectively with cross‑functional teams through iterative development.Proven ability todefine, 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/operatingLLMOps/MLOpsfoundations (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 inAWS,Databricks, and/orDataiku.Thermo Fisher ValuesDemonstrates Thermo Fisher’s values:Integrity, Intensity, Innovation, and Involvement.Equal Opportunity EmployerThermo 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.CompensationThe salary range estimated for this position based in Canada is $94,100.00–$141,125.00.Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.#J-18808-Ljbffr

📌 Senior Genai/Ai Solutions Architect - C$94,100 - C$141,125 A Year (Toronto)
🏢 Thermo Fisher Scientific
📍 Toronto