Software Developer
Fidelity Investments Canada ULC2 hours ago
Toronto, CanadaMid Level
Responsibilities
- Partner with business, product, and technology teams to define AI use cases and technical requirements.
- Build prototypes, proofs of concept, and production-quality generative AI and agentic applications, APIs, and services.
- Develop reusable Applied AI foundations for model access, RAG, enterprise knowledge, agent orchestration, tool use, evaluation, observability, and deployment.
- Build portable cloud-native components using AWS, Snowflake, and Kubernetes.
- Apply prompt and context engineering, LLMs, tools, memory, workflow orchestration, evaluations, guardrails, and observability.
- Embed security, privacy, risk, responsible AI, governance, human oversight, traceability, and monitoring into AI solutions.
- Evaluate emerging foundation models, agent frameworks, and AI engineering techniques for capability, security, governance, interoperability, performance, cost, and operational complexity.
- Apply software engineering practices including automated testing, security and quality gates, resilient design, error handling, monitoring, logging, fallbacks, and cost management.
- Support production AI services through observability, root-cause analysis, application and model monitoring, and continuous improvement.
- Contribute through design and code reviews, documentation, reusable examples, knowledge sharing, and cross-functional collaboration.
Requirements
- Degree in Computer Science, Software Engineering, Economics, or Mathematics, or equivalent working experience.
- At least 2 years of software development experience.
- Strong advanced Python skills for production-grade APIs, services, and applications.
- Experience delivering production software solutions and scalable cloud-native solutions using AWS, Snowflake, and Kubernetes.
- Proficiency in API development, containerization, infrastructure as code, automated testing, and software delivery pipelines.
- Knowledge of Java and/or JavaScript is an asset.
- Strong understanding of machine learning, generative AI, and agentic AI engineering principles and practices.
- Hands-on experience with LLMs, Retrieval-Augmented Generation, agent orchestration, tool integration, and prompt/context engineering is strongly preferred.
- Experience with AI evaluation, observability, monitoring, performance optimization, and cost management.
- Familiarity with MLOps/LLMOps, model and agent lifecycle management, and evaluation frameworks.
- Knowledge of AI security, privacy, responsible AI, and governance-by-design principles.
- Strong communication, stakeholder management, analytical problem-solving, and collaboration skills.
- AWS certification or equivalent hands-on cloud experience is an asset.
- Experience in financial services, mutual funds, or investment industries is preferred.
- Experience working in Agile or Scrum environments is an asset.
- Current work authorization for Canada is required.
Benefits
- 100% remote work and flexible working arrangements.
- Competitive total compensation with company RRSP contributions after six months, without employee matching.
- Comprehensive health benefits beginning the first day, including 100% employer-paid premiums and up to $5,000 annually for mental health services and therapy.
- Parental leave top-up to 100% of salary for 25 weeks.
- Up to $650 for home office equipment.
- Generous time off policy, including two paid volunteer days annually.
- Diversity and inclusion programs with Employee Resource Groups.
- Professional development opportunities including more than 11,000 training courses, tuition reimbursement, and monetary rewards for completing a required designation.