AI Native Developer (Agentic / Applied)

Role overview

Core responsibilities

• Develop multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability.
• Integrate LLM providers and models with fallback routing, token management, and cost and latency controls.
• Implement evaluation harnesses, prompt versioning, observability, and production cost and safety monitoring.
• Deliver client workshops, proofs of concept, coding sessions, deployments, and architecture walkthroughs.
• Create reusable patterns, accelerators, and playbooks; define AI accuracy, latency, safety, and cost metrics and communicate results to clients.

Required qualifications

• 7+ years of production software development experience and at least 1 year designing and deploying agentic AI solutions in production.
• Experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent; LLM APIs; and production RAG pipelines.
• Experience with LLM Ops, evaluation harness design, prompt versioning, and observability tooling.
• Experience with Kubernetes, Docker, microservices, serverless architectures, CI/CD, and infrastructure as code such as Terraform or Helm.
• Proficiency in Python; Java or an equivalent backend language is acceptable. Experience debugging and monitoring production systems is required.
• Experience deploying multiple agentic AI systems, standardizing relevant practices, building reusable delivery assets, and defining AI performance metrics.
• Experience working directly with client development teams in collaborative development environments.
• Bachelor's degree or college diploma in a related field. English is required for collaboration with multinational North American teams.

Compensation

• The posting lists annual base pay ranges of CAD 100,300 to CAD 216,700 for British Columbia, Ontario, and New Brunswick.
• Compensation varies by office location, role, skills, and experience; the stated range is a guideline and may be exceeded.