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AI Native Engineer

  • Vancouver, BC, Canada

Contract

This opening has closed.

The original listing is kept below for reference.

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Posting language
English
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Original job description

Archived listing. The details below describe a past opening.

AI Native Engineer

Location: Vancouver, BC Canada (Hybrid) - Local candidates only

Experience: 7+ Years | Type: Contract/Permanent

Role Summary

We're looking for a hands-on Senior AI Native Engineer to design, build, and ship production-grade AI agents, LLM-integrated applications, and developer productivity tooling on AWS. This is a coding role - the ideal candidate uses GitHub Copilot and/or Claude Code CLI daily and has taken agentic AI or LLM-based solutions beyond POC into real production environments, backed by solid cloud-native engineering, microservices, APIs, and DevOps fundamentals.

Key Responsibilities

  • Design, develop, and deploy production-grade AI agents and agentic workflows
  • Build LLM-powered applications and integrate AI into enterprise systems
  • Develop cloud-native services on AWS; build and maintain microservices, REST APIs, and event-driven integrations
  • Use GitHub Copilot and/or Claude Code CLI as part of daily engineering work
  • Implement agent workflows using LangGraph, LangChain, CrewAI, AutoGen, Strands, or Bedrock Agents
  • Build MCP (Model Context Protocol) integrations and develop MCP servers where applicable
  • Design and implement production-grade RAG solutions, including retrieval and evaluation
  • Integrate with AWS Bedrock, OpenAI, Anthropic, or other LLM APIs
  • Implement LLM observability, tracing, evaluation, and monitoring
  • Build AI guardrails, audit logging, and prompt-injection defenses
  • Own CI/CD pipelines and support deployment, monitoring, and continuous improvement
  • Participate in architecture discussions and code reviews as a strong individual contributor

Must-Have Qualifications

  • 7+ years hands-on software engineering (microservices, APIs, cloud-native, enterprise systems)
  • 3+ years hands-on AWS and DevOps/CI-CD experience
  • Proven experience personally building and deploying an AI agent, LLM integration, or agentic workflow to production
  • Active, current IC coding experience (within the last 6 months)
  • Demonstrated daily use of GitHub Copilot and/or Claude Code CLI, with real-world examples

Strongly Preferred

  • Hands-on MCP server development or MCP-enabled enterprise integration
  • Production experience with agent frameworks (LangGraph, LangChain, CrewAI, AutoGen, Strands, Bedrock Agents)
  • Strong AWS Bedrock production experience
  • Internal developer platform / engineering productivity tooling experience
  • Production RAG with measurable retrieval quality and eval frameworks
  • LLM observability/eval experience (Langfuse, LangSmith, Braintrust, W&B)
  • AI governance experience - guardrails, prompt-injection protection, access controls, audit logging
  • Secure enterprise integration design between AI agents and internal systems
More about this job

Responsibilities

Design, develop, and deploy production-grade AI agents and agentic workflows using LLMs. Build and maintain cloud-native services, microservices, and event-driven integrations on AWS.

Requirements

Requires 7+ years of software engineering experience with a strong focus on microservices, APIs, and cloud-native systems. Candidates must have 3+ years of hands-on AWS experience and proven success in deploying AI agents or LLM integrations into production.

Skills

  • AI Agents
  • LLM
  • AWS
  • Microservices
  • REST APIs
  • GitHub Copilot
  • Claude Code CLI
  • LangGraph
  • LangChain
  • CrewAI
  • AutoGen
  • RAG
  • AWS Bedrock
  • CI/CD
  • DevOps
  • Model Context Protocol

Visa sponsorship

Not detected in the job text

Categories

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

Keywords

  • AI Native Engineer
  • LLM
  • AI Agents
  • AWS
  • Microservices
  • REST APIs
  • GitHub Copilot
  • Claude Code CLI
  • LangGraph
  • LangChain
  • CrewAI
  • AutoGen
  • Bedrock Agents
  • Model Context Protocol
  • RAG
  • AWS Bedrock
  • CI/CD
  • DevOps
  • Observability
  • Tracing
  • Prompt-injection
  • Cloud-native
  • Enterprise Systems
  • Software Engineering
  • Agentic Workflows
  • Guardrails
  • Audit Logging
  • Event-driven
  • Engineering Productivity
  • MCP

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