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Software Developer, AI Engineering & SDLC Transformation

Job in Mississauga, Ontario, Canada
Listing for: Fidelity International
Full Time position
Listed on 2026-09-07
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 101000 - 118000 CAD Yearly CAD 101000.00 118000.00 YEAR
Job Description & How to Apply Below

Job Description Agentic Software Developer

You will be working on a 100% remote schedule as part of Fidelity's dynamic working arrangement. Current work authorization for Canada is required for all openings. At Fidelity, we've been helping Canadian investors build better financial futures for over 35 years. We offer individuals and institutions a range of trusted investment portfolios and services - and we're constantly seeking to find new and better ways to help our clients.

As a privately owned company, we boldly embrace innovation in all areas as we continue to grow our business into the future. Working with us means you'll be part of a diverse and dedicated group of people who make a real difference for our clients and communities every day. You'll have a wide range of opportunities to grow and develop your career in an inclusive environment where you'll feel valued and supported to be your best - both personally and professionally.

How

You'll Make an Impact

The Software Developer, AI Engineering & SDLC Transformation reports to the Manager, Applied AI and is responsible for applying generative AI and agentic engineering to transform the end-to-end software development lifecycle for Fidelity Investments Canada. This role goes well beyond AI-assisted coding. The individual will combine strong software engineering fundamentals with hand-on knowledge of modern AI and agentic technologies. They will work closely with business, product and engineering teams to understand how software is conceived and delivered today, identify friction and opportunities, and implement practical AI-enabled capabilities that improve developer experience, delivery speed, quality and control.

A key part of the role will be designing reusable agentic workflows, developer tools and engineering foundations that can reason over enterprise context, interact safely with approved tools and systems, and assist people throughout the SDLC.

What You Will Do
  • Partner with business, product, architecture, and engineering teams to identify and implement AI opportunities across the software development lifecycle.
  • Build AI-powered solutions that improve engineering productivity, software quality, and delivery outcomes.
  • Design and develop reusable agentic workflows, developer tools, and engineering foundations.
  • Implement capabilities for context retrieval, agent orchestration, tool integration, model evaluation, observability, guardrails, and secure execution.
  • Leverage AI to enhance requirements gathering, solution design, architecture, software development, and traceability across the SDLC.
  • Develop AI-assisted testing, quality assurance, defect analysis, and automated quality controls.
  • Ensure AI-enabled development capabilities adhere to security, privacy, governance, and risk management standards.
  • Evaluate and recommend AI models, agent frameworks, and developer tools for enterprise software engineering use cases.
  • Collaborate with development teams to pilot, refine, and scale AI-enabled engineering practices.
  • Measure and optimize outcomes using engineering, quality, adoption, and developer experience metrics.
  • Contribute to architecture reviews, engineering standards, documentation, and knowledge sharing initiatives.
The Expertise You Bring
  • Strong hand-on software engineering experience, particularly in Python
  • Experience developing and supporting production APIs, services, and developer tools
  • Knowledge of Java, JavaScript/Type Script, or other enterprise programming languages is an asset
  • Strong understanding of the full Software Development Life Cycle (SDLC)
  • Experience with AWS, Snowflake, and Kubernetes
  • Strong knowledge of Generative AI and Agentic AI engineering
  • Experience with source control, APIs, microservices, containers, CI/CD, automated testing, Infrastructure as Code (IaC), and Dev Sec Ops  practices
  • Understanding of security, privacy, and governance considerations related to AI agents and enterprise systems
  • Strong communication, collaboration, and interpersonal skills
  • Ability to quickly learn emerging AI models, agent frameworks, and development technologies
  • Proven ability to apply new technologies and translate them into practical engineering…
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