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
