Powered by AWS Bedrock and grounded in Bōde’s property, market and transaction data, Bōde proprietary AI removes complexity from every stage of homeownership. It helps people transact with confidence, understand their home’s performance and uncover more than $50,000 in potential value. For builders, Bōde’s platform reimagines what it means to be a strategic partner, delivering real time data, digital optimization and the seamless buyer experience in the Canadian market.

Every transaction becomes the beginning of a valuable long-term relationship, creating a more convenient and rewarding homeownership experience from the first search through every decision that follows. We're hiring the first dedicated technical owner of Bōde's AI layer. This is a senior, hands-on role: you'll set the technical direction for how Bōde AI is built and own the quality of what it produces.One thing that matters to how we build: we've learned that the best architecture is usually deterministic code for data preparation and validation, with a targeted model call only where it actually adds value, not reaching for "an agent" as the default answer to every problem.

Bode AI response quality: context engineering, prompt design, and retrieval tuning across our RAG pipeline, so answers are accurate, grounded, and cite their sources. Bōde AI AgentCore's managed capabilities without disrupting production.





Evaluation as a real discipline: you'll define rigorous and recurring performance standards for Bōde AI Cost and latency: what data and context gets sent to the model, token usage, and response time, including the reporting and controls you'll build around it. AI-layer security judgment calls: 4+ years building production software, including experience shipping LLM-backed features: applied work, not prototypes or side projects. ~ Strong prompt/context engineering skills, with a track record of measurably improving grounding, accuracy, or cost/latency in a live LLM system. ~ Hands-on experience with AWS Bedrock Agents or Bedrock AgentCore specifically, or deep, practical experience with a comparable agentic framework (LangGraph, Semantic Kernel, or a custom tool-orchestration system you built and ran in production).

Comfortable owning evaluation end to end: building golden sets, defining metrics, catching regressions before users do. ~ Solid backend engineering fundamentals (Node.js/TypeScript and Python); you'll be writing production code, not just prompts. ~ Highly valued: extensive experience with AWS Lex or another NLU/intent-classification system. We're looking for substantial time spent building and shipping with Bedrock, AgentCore, or a comparable agentic framework, not just strong fundamentals and quick learning.

📌 Senior Applied AI Engineer (Agent Systems) (Calgary)
🏢 Bōde
📍 Calgary