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WATAR-AI

Senior AI Engineer - Oncology Biometrics

Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Posting language: English
Posted: Nov 6, 2026

Original job description

About the company:

Our client is a global, science-driven biopharmaceutical company (top 10 worldwide)

focused on discovering, developing, and delivering innovative medicines and

healthcare solutions that improve patients’ lives. They are heavily investing in AI and

are building advanced Agentic AI solutions to accelerate scientific research and

decision-making across the organization.

Brief Job Profile Description

The role holder designs, builds, and owns AI agent workflows that run in real business processes for Oncology Biometrics, working within the AI Strategy and Innovation (OBM AI) team. Takes workflows from prototype to monitored, evaluated production services with a usable front end, and is accountable for their reliability, cost, and performance after release. Will mentor junior engineers and work with a cross-functional network of technical experts to deliver reliable, compliant AI solutions.

Typical Accountabilities

Design agent and multi-agent workflows end to end, including task decomposition, state and memory, tool design, routing, failure recovery, and human-in-the-loop checkpoints.
Build production backend services (Python, FastAPI), RAG pipelines, and MCP/API integrations with enterprise systems, and deliver the user-facing application, directly or with front-end engineers, including human review-and-approve steps.
Build evaluation and observability for each workflow (evaluation sets, quality metrics, regression testing, tracing, cost and latency monitoring) and apply guardrails against hallucination, prompt injection, and tool failure.
Deploy and operate services in production (containers, CI/CD, cloud), optimize model choice and routing for cost and latency, and follow up on incidents.
Deliver to GxP-aware standards, including traceability, audit trails, access control, versioned prompts and models, validation-supporting documentation, and human review, in line with AstraZeneca standards, responsible AI, and data privacy requirements.
Review code and designs, mentor junior engineers, and contribute reusable components and patterns to the wider team.

Qualifications and Skills

Essential: Degree in computer science, engineering, or a related discipline; 4–7+ years of software engineering, including 1–3 years building LLM or agentic systems; has shipped at least one agentic workflow into production use in a real business process (real users, operated after launch) and can describe what broke; deep, hands-on Python; production experience with LangGraph, LangChain, or an equivalent framework, RAG, and LLM APIs; demonstrated evaluation and observability practice; experience deploying services (containers, CI/CD, cloud); practical understanding of GxP-aware delivery.
Hands-on agentic AI experience. Someone who has built application with agent workflows, using tools such as Claude Core or Codex, and can help design and build our internal AI systems
Leadership: Someone who has led application development or small engineering team, working closely with business stakeholders.
Desirable: Fine-tuning (LoRA/QLoRA), model routing, or multimodal agents; Kubernetes and a major cloud AI service (Azure AI Foundry, AWS Bedrock, or GCP Vertex AI); React/Next.js and TypeScript; knowledge of 21 CFR Part 11, EU Annex 11, and computer system validation; clinical or statistical data experience (SAS/R/Python, CDISC); open-source contributions to agent or evaluation tooling.

Key Relationship to Reach Solutions

Internal: OBM AI Strategy and Innovation leadership and engineering team; Biometrics process owners and users of the workflows; R&D IT; Enterprise AI; Oncology Data Science & AI; Quality and Compliance Teams
External: AI and technology vendors and external service providers; open-source and developer communities

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More about this job

Responsibilities

Design, build, and operate production AI agent workflows for Oncology Biometrics, including backend services, RAG pipelines, integrations, and user-facing applications. Establish evaluation, observability, guardrails, and GxP-aware controls while optimizing production reliability, cost, and performance, and mentor engineers.

Requirements

Requires a degree in computer science, engineering, or a related discipline, 4–7+ years of software engineering experience, and 1–3 years building LLM or agentic systems, including at least one agentic workflow shipped and operated in production. Candidates need strong Python skills, experience with agent frameworks, RAG, LLM APIs, evaluation and observability, cloud deployment, and GxP-aware delivery; leadership experience is also sought.

Skills

Python
FastAPI
Agentic AI
Multi-Agent Workflows
LangGraph
LangChain
Retrieval-Augmented Generation
LLM APIs
Evaluation and Observability
Cloud Deployment
CI/CD
Containerization
MCP/API Integrations
GxP-Aware Delivery
Human-in-the-Loop Design
Technical Leadership

Visa sponsorship

Not detected in the job text

Keywords

Python
FastAPI
LangGraph
LangChain
Agentic AI
Multi-Agent Systems
Retrieval-Augmented Generation
LLM APIs
MCP
Evaluation Sets
Quality Metrics
Regression Testing
Observability
Tracing
Prompt Injection
Human-in-the-Loop
Containers
CI/CD
Cloud Deployment
GxP
Audit Trails
Access Control
Versioned Prompts
Responsible AI
Data Privacy
Kubernetes
Azure AI Foundry
AWS Bedrock
GCP Vertex AI
Oncology Biometrics

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