Software Developer, AI Engineer (Applied​/Software), AWS

Job Description

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.

As a Software Developer, Agentic AI Platform, at Fidelity Investments Canada, you will support the implementation, deployment and ongoing operation of components used in Agentic AI solutions across AWS and Snowflake. Working with senior team members and partner teams, you will help move approved Agentic AI use cases from prototype into controlled production environments. The role focuses on practical Python automation, cloud deployment, data integration, monitoring and production support rather than AI model development or research.

Support the implementation and integration of approved Agentic AI solutions within enterprise applications. Configure and maintain Python-based automation scripts and integration components used by Agentic AI workflows. Connect Agentic AI solutions with approved enterprise systems, services and data sources. Support retrieval workflows using enterprise documents and structured data stored or processed through platforms such as Snowflake. Assist with data integration workflows involving Snowflake, Informatica Cloud and approved enterprise data sources.

Troubleshoot integration issues involving model services, tools, data sources and data pipelines. Follow established engineering standards for version control, logging, exception handling, testing and documentation.

Support the deployment of Agentic AI workloads using existing CI/CD pipelines, containers and approved AWS and Snowflake deployment patterns. Assist with environment validation, testing, releases, troubleshooting and operational handover. Implement and maintain application logging, metrics, dashboards and alerts using established standards. Monitor service failures, runtime errors, retrieval performance, token usage and data-processing issues. Investigate technical issues involving integrations, prompts, tools, data retrieval, Snowflake workloads, Informatica Cloud workflows and supporting cloud services.

Collaborate with Data Engineering, Security, Architecture, Cloud and Ops teams to support data access, integrations and production readiness. Support applications through deployment and ongoing production operations while following approved security, access-control and environment standards. Maintain deployment documentation, operational procedures and support runbooks.

• University degree in Computer Science, Software Engineering, Information Technology or equivalent experience.
• 1-3 years of experience in software development, cloud engineering, Dev Ops or a related technical role.
• Good Python development skills and experience building scripts, automation solutions or integration components.
• Basic knowledge of Agentic AI concepts such as prompting, Retrieval-Augmented Generation, tool calling and structured outputs.
• Experience with Git, Git Hub Actions, CI/CD pipelines, Docker or Podman and SQL.
• Experience integrating REST services, backend systems or enterprise applications.
• Exposure to managed AI/ML platforms such as Amazon Bedrock, Agent Core, or Sage Maker, along with core AWS services is an asset.
• Familiarity with Agentic AI frameworks, MCP, observability/evaluation tools,…