AI Engineer
- Toronto, ON, Canada
- Greater Toronto and Hamilton Area, ON, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- Working hours
- 40 hours per week
- Posting language
- English
- Posted
Original job description
We are looking for an AI engineer for a short term contract (3 months, may be extended). The job will be to build agentic workflows that enhance current business processes.
AI and Agentic Engineering:
- LangGraph: state graphs, checkpointing, interrupt/resume for human-in-the-loop
- A2A protocol: agent-to-agent communication, agent cards, capability discovery
- MCP (Model Context Protocol): agent-to-tool integration
- RAG: retrieval-augmented generation, vector embeddings, knowledge bases
- Open Policy Agent (OPA): Rego-based policy-as-code, deny-by-default gatekeeping
- LiteLLM proxy: model-agnostic routing across OpenAI, Anthropic, Google, open-source
- Prompt versioning and decision audit logs: immutable, append-only, correlation IDs
Full-Stack Development:
- Node.js and Python for agent containers, orchestrators, gatekeepers
- React / Next.js for human-in-the-loop portals and approval dashboards
- Postgres (SQL) for platform schemas, agent schemas, LangGraph state persistence
AI-Accelerated Development:
- Claude Code, OpenCode, Cursor: prototype in hours, not weeks
Behavioral Competencies
- Business fluency, facilitation and discovery craft, trusted partner presence, analytical rigor, change leadership, narrative and knowledge capture.
- Works directly with client stakeholders
The Work
Building a multi-agent AI platform on Azure. The work covers the full stack:
- Shared orchestration foundation: human-in-the-loop portal, monitoring
- Multiple production agents built with LangGraph, each with human approval gates
- Data pipelines connecting agent workflows to external APIs and the client's data warehouse
Works alongside the Lead AI Engineer, a second AI Engineer building agents in parallel, and the client's engineering, data, and business teams. Daily standups with client engineers. Regular facilitation sessions with business stakeholders.
Logistics
- Duration: 3 months starting Oct 19, extendable
- Hours: 40 hours per week
- Location: Canadian resource, Eastern time zone. Regular client-facing meetings required (once per week, on site in the GTA).
More about this job
Responsibilities
Build a multi-agent AI platform on Azure, including shared orchestration, monitoring, human-in-the-loop portals, and production agents with approval gates. Develop data pipelines connecting agent workflows to external APIs and the client's data warehouse, while collaborating with engineering, data, and business stakeholders.
Requirements
The role calls for full-stack AI engineering experience with LangGraph, agent-to-agent and agent-to-tool integrations, RAG, policy-as-code, model routing, and audit logging. It also requires Node.js and Python, React or Next.js, PostgreSQL, stakeholder facilitation, and regular client-facing collaboration.
Skills
- LangGraph
- Agentic Workflows
- Agent-To-Agent Communication
- Model Context Protocol
- Retrieval-Augmented Generation
- Vector Embeddings
- Open Policy Agent
- LiteLLM
- Node.js
- Python
- React
- Next.js
- PostgreSQL
- Azure
- Human-in-the-Loop Systems
- Data Pipelines
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Consulting
Keywords
- Artificial Intelligence
- Agentic Engineering
- LangGraph
- State Graphs
- Checkpointing
- Human-in-the-Loop
- Agent-To-Agent Protocol
- Agent Cards
- Capability Discovery
- Model Context Protocol
- Retrieval-Augmented Generation
- Vector Embeddings
- Knowledge Bases
- Open Policy Agent
- Rego
- Policy-As-Code
- LiteLLM Proxy
- Model Routing
- Prompt Versioning
- Decision Audit Logs
- Node.js
- Python
- React
- Next.js
- PostgreSQL
- Azure
- Data Pipelines
- External APIs
- Data Warehouse
- Claude Code