We are looking for a Senior AI Engineer to join our team building an Agentic AI Platform for enterprise clients in regulated industries. Our team works spec-first and ship-oriented: we write it down, build it properly, and run it in production.

Role: Senior AI Engineer (Software Engineering Focus)

Job type: Contract

Location: Hybrid, Canada (required)

Experience: 5+ years full-stack development in React/Python (required); 3+ years building production AI/GenAI applications (required)

Rate: Competitive contract rate based on experience THE ROLE

We are hiring a software engineer first, who has added AI to a strong engineering toolkit. You will build and run a production Agentic AI Platform for regulated enterprise clients, and the hard parts of this job are engineering problems: clean APIs, reliable services, testable code, safe deployments and systems that stay up. LLMs, retrieval and AI agents are components in the system you build, not the whole job.

We care less about which model you prompted and more about how you designed the service around it, how you tested it, and what happened when it broke at 2 a.m.

You will work across the stack: React frontend → Node.js / Python APIs → FastAPI AI services → LLM and RAG pipelines → enterprise data → CI/CD and cloud production.

This is not a data science, ML research, prompt engineering, low-code or solution architecture role. You will write and review code every day.

WHAT YOU WILL DO

Engineering (most of your time) - Design and build backend services and APIs in Python (FastAPI) and Node.js/TypeScript, with clear contracts, versioning and error handling.

- Build React frontends for AI-assisted workflows, including streaming responses, citations and human review screens.
- Model data and integrate with enterprise systems: SQL and NoSQL stores, internal APIs, document repositories and identity providers.
- Write unit, integration and end-to-end tests; keep CI/CD pipelines green and deployments repeatable.
- Own production readiness: logging, tracing, monitoring,



alerting, retries, rate limits, security reviews and cost controls.
- Lead and take part in code reviews, design reviews and technical specs before code is written.
- Debug and support live systems, run root-cause analysis, and fix the underlying problem.

AI integration

- Build agentic capabilities as well-engineered services: multi-step agent workflows, tool calling, LLM orchestration, RAG pipelines, embeddings and vector search over enterprise data.
- Treat model behaviour as something to test: build evaluation harnesses for accuracy, hallucination, regression and guardrails, and run them in CI.
- Add traceability and audit logging so every AI output can be explained to compliance and risk teams.

Collaboration

- Work with product, QA, security, compliance and client stakeholders to turn requirements into specs and shipped software.

WHAT YOU BRING

- Software engineering foundation (required) - 5+ years of hands-on full-stack software development, building and maintaining production systems used by real customers. - Strong Python and TypeScript/JavaScript; production experience with FastAPI and Node.js, and with React on the frontend.
- Solid grasp of computer science fundamentals, data structures, design patterns and software architecture.
- Experience designing REST or GraphQL APIs, microservices, async processing and event-driven systems.
- Relational and NoSQL database design, query tuning and data migrations.
- Automated testing as a habit: unit, integration and end-to-end, with good coverage of the risky paths.
- Git, CI/CD, Docker, and deploying and operating workloads on AWS.
- Production operations:



observability, incident response, performance tuning and security best practices.
- AI experience (required) - 3+ years building and operating production-grade AI, ML or GenAI applications.
- Hands-on with RAG, embeddings, vector databases and LLM APIs (OpenAI, Anthropic, Azure OpenAI or Bedrock).
- Experience testing and evaluating AI output, not just generating it.

NICE TO HAVE

- Experience in finance, risk, governance or compliance platforms (SOX, audit, controls).
- Building systems where accuracy, traceability, auditability and data privacy are requirements, not extras.
- Agent frameworks and orchestration (LangGraph, LlamaIndex, MCP or similar), used with a critical eye.

HOW WE EVALUATE

- We hire for engineering depth first, then AI experience. Expect the process to test how you build software, not how many AI tools you can name. - Engineering track record: years of shipping and maintaining production code, and named systems you owned (not mostly notebooks, POCs, hackathons or courses).
- Code quality: clean, tested code in a live exercise or a repo you can share (not code that only works on the happy path).
- System design: transparent APIs, data models, failure handling and trade-offs (not diagrams with no detail on how parts fail or scale).

HOW TO APPLY

- Apply through this posting with your resume and a short note. In the note, describe one production system you built: what it did, your part in it, how it was tested and deployed, and one thing that went wrong in production. A GitHub link or code sample is welcome. Not the right fit if you are looking mainly for research, prompt engineering, architecture-only or low-code work. This role writes code every day.

Pay: $60.00-$70.00 per hour Expected hours: 37.5 per week

Experience

- Software Engineering: 5 years (required)
- AI Engineering: 3 years (required)

Location:
- Toronto, ON (preferred)

Work Location: Hybrid remote in Toronto, ON (Toronto District)

📌 Senior AI Engineer (Software Engineering Focus) (Toronto)
🏢 Aqila Systems
📍 Toronto