Software Engineer-AI Platforms

Team: Development

Location: Toronto, ON

Commitment: Full Time

Workplace Type: hybrid

Knowledge, Experience, Requirements:

Required

• 2–5 years of professional software engineering experience, including shipping production features across frontend and backend

• Proficiency in Node.js and TypeScript/JavaScript

• Experience building responsive web UIs with a modern framework such as React, including state management and API integration

• Ability to build and consume well-typed REST or GraphQL APIs in Node.js and TypeScript, with sound handling of authentication, error handling, and data transformation

• Hands-on experience building at least one application or feature using large language models via platforms such as AWS Bedrock, OpenAI, Anthropic, or similar

• Working understanding of tools, function calling, and agents, and how they let LLM systems take action against existing APIs

• Practical experience with prompt engineering and iterating on prompts to improve output quality

• Familiarity with Retrieval-Augmented Generation (RAG) concepts, embeddings, and vector-based search

• Comfort working in an AI-first development environment, using AI tools for code generation, refactoring, test creation, and documentation, and reviewing their output critically

• Experience working with relational databases and writing efficient queries

• Solid grasp of data structures, algorithms, and fundamentals of system design

• Good debugging skills across the browser, server, and network

• Experience writing unit and integration tests and working with CI/CD pipelines

• Clear communication and collaboration skills in an agile, team-based environment

• Bachelor's degree in Computer Science, Engineering, or a related technical discipline preferred, or equivalent practical experience

Nice to have

• Exposure to building or consuming Model Context Protocol (MCP) servers or similar AI integration layers

• Experience with LangChain, LangGraph, or similar orchestration frameworks

• Familiarity with LLM evaluation approaches, guardrails, or output monitoring

• Experience with AWS services (e.g., Lambda, ECS, S3) or another major cloud provider

• Exposure to observability tooling such as Datadog or CloudWatch

• Interest in or exposure to EHS, compliance, or safety software

Success Criteria:

• Delivers well-scoped, production-ready AI-powered features end to end, from UI to backend service, with solid test coverage and minimal rework

• Builds intuitive user experiences that present LLM outputs clearly, including loading states, error states, and ways for users to review or correct AI-generated results

• Implements LLM-driven workflows using services such as AWS Bedrock and LangChain, following patterns set by senior engineers

• Contributes to MCP servers and tool integrations that expose existing APIs to AI systems, with appropriate authentication, input validation, logging, and failure handling

• Applies prompt engineering techniques to improve accuracy and consistency, and uses evaluation results to measure improvements

• Implements guardrails and monitoring for LLM outputs as defined by the team's standards

• Validates and refines AI-generated code before submitting it for review, and owns its quality

• Breaks down defined product requirements into clear tasks and estimates, and raises ambiguity early

• Communicates progress, blockers, and tradeoffs clearly to engineering peers and product partners

• Participates actively in code reviews, both giving and receiving feedback constructively

• Shares useful AI workflows and learnings with the team through documentation and internal discussions

• Steadily grows ownership, moving from scoped features toward larger components and system-level design

• Contributes positively to team culture by collaborating effectively and fostering continuous learning

Compensation:

Annual Base Salary Range of:
Software Engineer- 110k-130k CAD
Senior Software Engineer- 130k-150k CAD
 
Annual Bonus Opportunity of 10%

Location:

We’re a remote-first team that gets together in our North York office in Toronto every Tuesday, and as needed for in-person team events. The person in this role will be willing and able to commute to the office one day a week, and comfortable working remotely the rest of the time.