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About the Role
This hands-on engineering role focuses on designing, building, testing, and deploying practical, secure, and governed AI solutions, with a strong emphasis on generative AI, agentic AI, and modern software engineering. You will contribute to reusable Applied AI foundations that can be scaled across multiple business use cases, translating rapidly evolving AI capabilities into production-ready solutions.
Responsibilities
- Partner directly with business, product, and technology teams to understand business problems and translate them into well-defined AI use cases and technical requirements.
- Build rapid prototypes and proofs of concept, and develop successful ideas into production-quality AI and agentic applications, APIs, and services.
- Build and extend Applied AI foundations, including reusable patterns for model access, RAG and enterprise knowledge, agent orchestration, tool use, evaluation, observability, and deployment.
- Develop cloud-native components using technologies such as AWS, Snowflake, and Kubernetes.
- Design modular and portable AI components that preserve strategic flexibility across models, frameworks, and vendors.
- Collaborate with Fidelity International and Architecture teams to reuse and extend enterprise capabilities.
- Apply modern agentic engineering practices, including prompt and context engineering, LLMs, APIs, tools, memory, RAG, workflow orchestration, evaluations, guardrails, and observability.
- Build AI solutions with security and governance embedded from the beginning, working closely with AI Governance, Security, Privacy, Risk, and Architecture on data access, model and tool usage, human oversight, traceability, monitoring, and other required controls.
- Continuously evaluate emerging foundation models, agent frameworks, and AI engineering techniques through hands-on experimentation.
- Assess technologies based on capability, security, governance, interoperability, performance, cost, and operational complexity, and turn promising approaches into reusable production patterns.
- Apply strong software engineering practices across AI applications, including automated testing, CI/CD, security and quality gates, resilient design, error handling, monitoring, logging, fallbacks, and cost management.
- Support production AI services through observability, root-cause analysis, and continuous improvement, monitoring application health as well as model and agent quality, latency, errors, and cost.
- Contribute to a strong Applied AI engineering culture through design and code reviews, technical discussions, documentation, reusable examples, knowledge sharing, and collaboration across business, data, architecture, security, governance, and international teams.
Requirements
- Current work authorization for Canada is required.
- Strong expertise with advanced Python skills for developing and supporting production-grade APIs, services, and applications.
- Experience building and deploying scalable cloud-native solutions using AWS, Snowflake, and Kubernetes.
- Proficiency in API development, microservices architecture, containerization, CI/CD pipelines, Infrastructure as Code (IaC), and automated testing.
- Knowledge of Java and/or JavaScript is considered an asset.
- Strong understanding of Machine Learning, Generative AI, and Agentic AI Engineering principles and practices.
- Hands-on experience with LLMs, Retrieval-Augmented Generation (RAG), agent orchestration, tool integration, and prompt/context engineering.
- Experience with AI evaluation, observability, monitoring, performance optimization, and cost management.
- Familiarity with MLOps/LLMOps, including model and agent lifecycle management and evaluation frameworks.
- Knowledge of AI security, privacy, responsible AI, and governance-by-design principles.
- Excellent communication, stakeholder management, analytical problem-solving, and continuous learning capabilities, with the ability to collaborate effectively across technical and business teams.
- Degree in Computer Science, Software Engineering, Economics or Mathematics or equivalent working experience.
- 2+ years of experience in software development, preferably in the financial services/mutual fund/investment industry.
- Demonstrated hands-on experience delivering production software solutions, with practical experience in AI/ML, generative AI or agentic applications strongly preferred.
- AWS certification or equivalent hands-on cloud experience is considered an asset.
- Experience working within Agile or Scrum environments is an asset.
Skills
- Python
- AWS
- Snowflake
- Kubernetes
- API development
- Microservices architecture
- Containerization
- CI/CD pipelines
- Infrastructure as Code (IaC)
- Automated testing
- Java
- JavaScript
- Machine Learning
- Generative AI
- Agentic AI Engineering
- LLMs
- Retrieval-Augmented Generation (RAG)
- Agent orchestration
- Tool integration
- Prompt engineering
- Context engineering
- AI evaluation
- Observability
- Monitoring
- Performance optimization
- Cost management
- MLOps
- LLMOps
- AI security
- AI privacy
- Responsible AI
- AI governance
- Agile
- Scrum
Location
- Remote
Work Type
- Remote
- Full-time
Experience Level
- 2+ years of experience in software development
Education Level
- Degree in Computer Science, Software Engineering, Economics or Mathematics or equivalent working experience
Salary/Compensations
- $101,000 to $118,000
Benefits
- Competitive compensation package
- Base Salary and Discretionary Performance Bonus
- RRSP Contribution (after 6 months of employment, no employee matching required)
- Flexible working arrangements
- Competitive total compensation
- Company contributions to your group RRSP without a matching requirement from you
- Comprehensive health benefits that start on your first day, with 100% employer-paid premiums
- Up to $5000 annually for mental health services and therapy
- Parental leave top-up to 100% of your salary for a period of 25 weeks
- Up to $650 for home office equipment
- Generous time off policy
- Two paid days annually to volunteer at a charity of your choice
- Diversity and inclusion programs
- Extensive professional development opportunities
- Access to over 11,000 training and development courses
- Tuition reimbursement
- Monetary rewards for completing a required designation
About the Company
- Fidelity has 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.
- 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.
- We are proud to be recipients of numerous awards including Canada's Top 100 Employers, Greater Toronto's Top Employers, Canada's Top Family-Friendly Employers, Canada's Top Employers for Young People, Great Place To Work® Certified, LinkedIn Top Companies in Canada, Human Resource Director (HRD) - Best Place To Work, Canadian Compassionate Companies, Benefits Canada's Workplace Benefits Award, TalentEgg National Recruitment Excellence Award, and Canadian HR Reporter's Most Innovative HR Team.
Equal Opportunity
- Fidelity Canada is an equal opportunity employer.
- Fidelity Canada is committed to fostering a diverse and inclusive workplace.
- We will consider all qualified applicants for employment regardless of race, color, religion, sex, sexual orientation, gender identity or expression, national or ethnic origin, age, disability, family status, protected veterans’ status, Aboriginal/Native American status or any other legally-protected ground.
- Fidelity Canada welcomes and encourages applications from people with disabilities.
- Accommodations are available on request for candidates taking part in the selection process.