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Senior Software Engineer, AI Enablement & Solutions

  • Toronto, ON, Canada

Base Salary Range: 90,489 to 132,711 CAD · Full-time

This opening has closed.

The original listing is kept below for reference.

Job details

Pay
Base Salary Range: 90,489 to 132,711 CAD
Job type
Full-time
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

Job Description

The Group

Morningstar DBRS provides independent credit ratings, research, and risk insights to market participants around the world. As AI becomes a practical tool for research, analysis, and operational workflows, we're building the foundations that allow teams across the business to use it responsibly and effectively.

This team sits at the intersection of software engineering, AI, and business transformation. We build the platforms, services, and tools that help Morningstar DBRS move from experimentation to real-world adoption.

The Role

We're looking for a Senior Software Engineer to help shape how AI is used across Morningstar DBRS.

This is not a research role and it is not focused on building isolated proofs of concept. You'll develop the shared infrastructure, services, and applications that allow teams across the organization to deploy AI capabilities into production. You'll work closely with engineers, product partners, and business stakeholders to identify opportunities where AI can improve workflows, reduce manual effort, and support better decision-making.

You'll have significant influence over technical direction while remaining hands-on in the design, development, and operation of the systems you build.

What you'll be doing

  • Design and build production AI applications using AWS Bedrock and related AWS services, with a focus on reliability, security, and maintainability.
  • Develop AI agents, MCP servers, APIs, and shared platform capabilities that enable other teams to build and deploy AI-powered solutions.
  • Partner with business and technology teams to understand complex workflows and identify opportunities where AI can deliver measurable improvements.
  • Evaluate and implement approaches such as tool use, retrieval-based architectures, orchestration frameworks, and model evaluation techniques to improve application performance and accuracy.
  • Modernize existing Python-based applications and integrate AI capabilities into products and workflows already used across Morningstar DBRS.
  • Contribute to technical decisions, engineering standards, and delivery planning while helping guide less experienced engineers when needed.

What we're looking for

  • Strong software engineering fundamentals with experience building and operating production applications in AWS.
  • Professional experience developing applications and services in Python.
  • Experience delivering AI-powered applications beyond experimentation, including deploying solutions used by internal or external customers.
  • Hands-on experience with AWS Bedrock or comparable enterprise AI platforms and the surrounding ecosystem of model integration, evaluation, and monitoring.
  • Experience designing and consuming APIs, building distributed services, and integrating with enterprise systems.
  • A practical approach to software architecture, testing, observability, and operational support.
  • Ability to work with both technical and non-technical stakeholders to translate business problems into software solutions.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Base Salary Range: 90,489 to 132,711 CAD

Bonus Target Percentage: 15%

If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker.

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

More about this job

Responsibilities

You will design and build production-ready AI applications and shared infrastructure to support business workflows. You will collaborate with cross-functional teams to integrate AI capabilities into existing products while ensuring system reliability and security.

Requirements

The role requires strong software engineering fundamentals with professional experience in Python and AWS. Candidates must have a proven track record of deploying AI-powered applications into production environments.

Skills

  • Software Engineering
  • Python
  • AWS Bedrock
  • AI Agents
  • API Development
  • Distributed Systems
  • Cloud Infrastructure
  • System Architecture
  • Model Evaluation
  • Retrieval-based Architectures
  • Orchestration Frameworks
  • Observability
  • Technical Leadership
  • Stakeholder Management
  • Production Deployment

Benefits

  • Hybrid work environment
  • Flexibility

Visa sponsorship

Not detected in the job text

Categories

  • Software
  • Technology
  • Engineering
  • Data & Analytics
  • Finance & Accounting

Keywords

  • Software Engineering
  • AI Enablement
  • AWS Bedrock
  • Python
  • AI Agents
  • MCP Servers
  • APIs
  • Distributed Services
  • Cloud Computing
  • System Architecture
  • Model Evaluation
  • Monitoring
  • Observability
  • Production Systems
  • Data Engineering
  • Machine Learning
  • Software Development
  • Technical Leadership
  • Credit Ratings
  • Financial Research

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