AI Engineer

Job summary

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.

Job details

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).

What you’ll do

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.

Listed skills

• Node.js · Preferred
• Python · Preferred
• React · Preferred
• Next.js · Preferred
• PostgreSQL · Preferred
• Microsoft Azure · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• 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

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Consulting