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Job Description & How to Apply Below
AI and Agentic Engineering
Lang Graph: state graphs, checkpointing, interrupt/resume for human-in-the-loop
A2A protocol: agent-to-agent communication, agent cards, capability discovery
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
AI-Accelerated Development
Claude Code, Open Code, Cursor: prototype in hours, not weeks
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 Lang Graph, 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).
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