AI Engineer

Reference Number : R2868511

Position title : AI Engineer

Department: Commercial Data Science

Location: Toronto,ON ( Flexible working - 40% home office / week)

About the job

Ready to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world.

About the Sanofi Digital:

We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the centre of our ambitions.

Sanofi’s Digital organization’s mission is to transform Sanofi into a data-first and AI first organization by empowering everyone with good data. Through custom developed AI products built on world class data foundations and platforms, the team builds value and a unique competitive advantage that scales across our markets, R&D and manufacturing sites. The team is located in major hubs in Paris, Lyon, Barcelona, Cambridge, Toronto, Budapest and Hyderabad. Join a dynamic, fast paced and talented team, with world class mentorship, using AI to chase the miracle of science.

We are seeking a skilled AI Engineer to drive innovation and impact at the intersection of AI and Commercial operations. This role will be a part of the Digital Commercial Advanced Analytics and AI team, which operates under the Digital Global Business Units and is an integral part of Sanofi Digital Organization.

About Sanofi

We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Main Responsibilities:

Design, develop, deploy, and support scalable Generative AI and Agentic AI solutions aligned with strategic priorities across Sanofi's Global Business Units

Architect and implement Retrieval-Augmented Generation (RAG) solutions, multi-agent systems, and AI copilots leveraging enterprise data and knowledge assets

Collaborate closely with product owners, business stakeholders, architects, data scientists, data engineers, and software engineers to deliver AI products that create measurable business value

Work on prioritized impactful business use cases such as

Agentic AI powered Market Research & Competitive Intelligence platform

Autonomous agents for omnichannel engagement

AI & GenAI driven transformation of market access and payer strategies

Conversational AI for data interactions and insights (Talk-to-data capabilities)

Development of unified platform of sales, marketers and MSL users powered by multi-agent systems

Enhancing the patient journey through intelligent and personalized support

Design reusable AI components, frameworks, libraries, and services that accelerate enterprise AI solution development

Build and optimize agentic workflows, prompt engineering strategies, orchestration frameworks, and tool integrations to improve AI application performance and reliability

Develop and maintain production-ready code following AI engineering best practices, including testing, CI/CD, observability, and documentation standard

Contribute to the evolution of AI platform, and enterprise data foundation strategies

Monitor, evaluate, and continuously improve AI application quality, performance, scalability, and user adoption

Ensure AI solutions comply with Responsible AI, security, privacy, governance, and regulatory requirements

Stay current with emerging AI technologies, foundational models, frameworks, and engineering practices, and identify opportunities to incorporate innovations into existing products and platforms

Communicate technical concepts, architectural decisions, and solution outcomes effectively to both technical and business audiences

Mentor and coach junior AI engineers, software engineers, data scientists, and interns while fostering engineering excellence and knowledge sharing

About you

Required Qualifications:

Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related quantitative discipline

3+ years of experience designing, building, and deploying AI/ML solutions in production environments, with at least 2+ years of hands-on experience developing GenAI, LLM, RAG, or Agentic AI applications

Strong software engineering and programming skills in Python or Java or other enterprise programming languages SQL/NoSQL query, familiarity with Spark, REST APIs, Golang, NodeJS, Angular, Typescript etc.

Experience developing AI applications using modern frameworks and libraries such as LangChain, LangGraph, Transformers, and vector database technologies

Strong understanding of agentic AI architectures, multi-agent systems, prompt engineering, tool/function calling, workflow orchestration, and AI application evaluation frameworks

Proficiency working with structured, semi-structured, and unstructured data stored in enterprise platforms including Snowflake, Pinecone, object stores (e.g., Snowflake, AWS DocumentDB, S3, AWS RDS) or similar databases

Experience developing and deploying production-grade AI applications with a focus on scalability, reliability, observability, security, and performance optimization

Understanding of AI/ML lifecycle management, including model deployment, monitoring, evaluation, governance, and continuous improvement practices

Experience working with cloud platforms such as AWS, or GCP, leveraging cloud-native AI, data, and application services

Experience with containerization and modern engineering tools such as Docker, Kubernetes (AWS EKS/ECR/Eventbridge), CI/CD pipelines, and source control platforms (GitHub, DevOps)

Familiarity with DevOps tooling like SonarQube, Checkmarx, Artifactory, AWS CloudWatch, Datadog, Jfrog, Grafana, Thanos, Prometheus

Experience integrating AI solutions with enterprise systems through REST APIs, microservices, and event-driven architectures

Knowledge of regulatory, compliance and ethical considerations in AI/GenAI

Nice to be already involved in an Agile/Scrum environment and Comfortable utilizing tools like Jira & Confluence

Functional Skills:

Ability to communicate complex AI, GenAI, and Agentic AI concepts effectively to both technical and non-technical stakeholders

Understanding of end-to-end AI product development initiatives and collaborating across engineering, product, business, data, and platform teams

Ability to define technical architecture, identify dependencies, manage risks, and resolve blockers across cross-functional Agile teams

Strong problem-solving, systems-thinking, and solution design capabilities with a focus on delivering measurable business outcomes

Experience mentoring junior AI engineers, data scientists, or technical team members

Excellent written and verbal communication skills, including technical documentation, architecture reviews, and leadership-level presentations

Ability to translate business requirements into scalable, maintainable, and production-ready AI solutionsExperience working in global, cross-functional, and multicultural teams within complex enterprise organizations

Nice to have professional certification such as AWS certified ML Engineer or SnowPro Data Scientist Certification

Ability to thrive in a fast-paced, rapidly evolving AI landscape while managing multiple priorities and