Generative AI Cloud Operations Engineer - Evinova

Evinova; Mississauga; On-site; CAD 156,738 - 205,718; Full time

Benefits offered by this job

Competitive salary including annual bonus

4 weeks paid vacation

Retirement savings program

Job summary

A global health-tech business in Canada is seeking a Generative AI Cloud Operations Engineer to lead AI operations for their trial management SaaS product. Responsibilities include developing AI operation systems and ensuring the optimization of generative AI applications. Ideal candidates will have at least 2 years of relevant experience and a strong background in deploying AI agents. This role offers a competitive salary and a collaborative work culture focused on innovation.

Qualifications

• Minimum of 2 years deploying and maintaining generative AI agents.
• Experience with data science lifecycle and production projects.
• Proficiency in eval tools for LLMs.

Responsibilities

• Drive creation of operational capabilities for generative AI.
• Develop and manage AI Ops systems for trial optimization.
• Integrate proxies and optimize pipelines for performance.

Skills

Understanding of generative AI applications

Software engineering in Python/TypeScript

Collaboration with cross-functional teams

Strong communication skills

Education

HS Diploma or GED

Tools

AWS services

Docker

Kubernetes

LangChain

LangGraph

Job description

Job Title

Generative AI Cloud Operations Engineer – Evinova

Location

Toronto, ON

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge‑sharing, ambitious thinking, and innovation – ultimately providing employees with the opportunity to work across teams, functions, and even the globe.

We are part of a new Health‑tech business, Evinova, a fully‑owned subsidiary of AstraZeneca Group. Evinova delivers market‑leading digital health solutions that are science‑based and evidence‑led. We are building a new Health‑tech business that combines deep scientific expertise with digital and artificial intelligence to serve a wider healthcare community.

Introduction to Role

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed platform team that will spearhead the design, creation, and operational excellence of our LLM‑based agent deployments, multi‑agent orchestration, and conversational AI systems pipelines. This team is responsible for design, implementation, deployment, health, and performance of all LLM‑based applications, managing ML/AI and cloud resources, and automating operations through infrastructure‑as‑code and CI/CD pipelines.

As a Generative AI Cloud Operations Engineer for clinical trial design, planning, and operational optimization, you will lead the development and management of AI operations systems for our trial management and optimization SaaS product. You will collaborate closely with AI Engineers to transition projects from research into production‑grade AI capabilities and optimize model deployment, governance, and infrastructure performance.

Accountabilities

Operational Excellence

• Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
• Design and implement resilient cloud generative AI agent operational capabilities to maximize system A‑abilities (Learnability, Flexibility, Extensibility, Interoperability, Scalability).
• Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data‑driven strategy, comprehensive analytics, and predictive capabilities at the tree‑and‑forest level of our generative AI‑based systems, workloads and processes.

ML/AI Cloud Operations and Engineering

• Develop and manage GenAI Ops systems for clinical trial design, planning and operational optimization.
• Integrate LLM proxies/routers including LiteLLM Proxy/Router or other solutions.
• Ensure proper RAG pipeline optimization and scaling.
• Integration of token usage, latency, response quality, and hallucination detection tools at a platform level.
• Partner closely with AI Engineers and data scientists to shepherd projects from embryonic research stages into production‑grade agentic generative AI capabilities.
• Leverage and teach modern tools, libraries, frameworks and best practices to design, validate, deploy and monitor generative AI agents in production (including LangChain, LangGraph, Google ADK, Langfuse, DSPy, Arize Phoenix, Pinecone, Weaviate, Splunk, Grafana, Prometheus, Xray)
• Enhance system scalability, reliability, and performance through effective infrastructure and process management.
• Ensure that any prediction we make is backed by deep exploratory data analysis and evidence, interpretable, explainable, safe, and actionable.
• Leverage Vertex AI, Azure Foundry, OpenAI, Anthropic, and other foundation model platforms to provide reliable and stable access to LLMs.

Personal Attributes

• Customer‑obsessed and passionate about building products that solve real‑world problems.
• Highly organized and detail‑oriented, with the ability to manage multiple initiatives and deadlines.
• Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive.
• Know when to ask for help and when to help others proactively.

Essential Skills/Experience

• HS Diploma or GED.
• Minimum of 2 years deploying and maintaining generative AI agents or GenAI‑based workflows/applications in production.
• Deep understanding of challenges in deploying generative AI applications and agents.
• Closely follows frontier developments in generative AI and GenAI tooling, techniques, and technologies.
• Deep understanding of the data science lifecycle (DSLC) and ability to shepherd data science projects from inception to production within the platform architecture.
• Expert in evals tools for LLMs such as Arize Phoenix, Langfuse, Braintrust, Freeplay or similar.
• Expert in CDK for Python and/or TypeScript.
• Strong software engineering abilities in Python/TypeScript.
• Expert in AWS services and containerization technologies like Docker and Kubernetes.
• Experience deploying GenAI agents using frameworks such as LangChain, LangGraph, LlamaIndex, Google ADK, or Strands Agents.
• Ability to collaborate effectively with engineering, design, product, and science teams.
• Strong written and verbal communication skills for reporting and documentation.
• Proven track record of deploying algorithms and machine learning models into production environments.
• Demonstrated ability to work closely with cross‑functional teams, particularly data scientists.

Great People want to work with us! Find out why:

• GTAA Top Employer Award for 10 years.
• Top 100 Employers Award.
• Canada’s Most Admired Corporate Culture.
• Learn more about working with us in Canada.
• View our YouTube channel.

Why Evinova?

Evinova is a global health‑tech business, part of the AstraZeneca group. Our goal is to accelerate the delivery of life‑changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment.

By bringing our solutions to the wider life sciences community, we can build more unified approaches, simplify workloads, and benefit patients broadly. Join us on our journey to build a new kind of health‑tech business that resets expectations of what a biopharmaceutical company can be.

Compensation & Benefits

Annual base salary ranges from $114,622.40 to $150,441.90. The base pay offered will vary depending on multiple individualized factors, including your skills and experience. Permanent positions offer an annual variable pay bonus, equity‑based long‑term incentive program (if applicable), a competitive flex‑benefits & retirement savings program, 4 weeks paid vacation, and annual personal days. Fixed‑term contract/temporary positions offer a contract benefits program.

We are using AI as part of the recruitment process.

This advertisement relates to a current vacancy.