[Hiring] Staff AI Builder @Robots and Pencils

Role Description

We’re looking for a Staff AI Builder to lead the design and delivery of AI/ML systems. This role is ideal for an experienced engineer who thrives on architectural decisions, can confidently own systems end-to-end, and contributes to technical leadership across the team.

In this role, you will work as a key technical leader on a cross-functional team, defining AI architecture, leading model development and optimization, and solving challenging integration problems. You’ll be joining real, in-flight work where reliability, security, and scalability are critical. You’ll establish engineering standards, raise the bar on how we build AI systems, and contribute to the technical decisions that shape how our AI work scales over time.

What You'll Do

• Agentic & GenAI Engineering
  • Design and build agentic workflows — reasoning loops, tool/function calling, and orchestration across single- and multi-agent architectures.
  • Build and maintain RAG pipelines: chunking strategy, embeddings, vector search (OpenSearch), re-ranking, and staleness/refresh handling for dynamic knowledge sources.
  • Integrate with AWS Bedrock and Agent Core, including MCP-based tool design.
  • Write and iterate on production system prompts — structured role framing, output constraints, and few-shot design.
  • Build eval and observability into every agent you ship: golden datasets, RAGAS-style metrics, LLM-as-judge, and tracing via LangFuse/LangSmith or equivalent.
  • Design for LLM failure, not just LLM success: retries with backoff and jitter, circuit breakers, fallback models, and a clear user-facing story when something upstream degrades.
• Full-Stack & Platform Engineering
  • Build backend services in Python and Node.js, including serverless architectures (AWS Lambda, API Gateway).
  • Design DynamoDB single-table schemas — composite keys, transactional writes — for conversation state, agent memory, and session history.
  • Support event-driven orchestration (Step Functions, SQS, EventBridge) for asynchronous agent operations.
  • Contribute to frontend integration points so agentic features land cleanly for end users.
  • Support deployment, monitoring, and production troubleshooting in cloud-native environments (AWS, Docker).
• Collaboration & Technical Leadership
  • Bring informed technical judgment to architecture discussions.
  • Partner with product, design, and delivery leads across global teams to scope and ship features end-to-end.
  • Mentor other engineers on the pod and help raise the bar on agentic engineering practices.
  • Own assigned features and releases end-to-end — including debugging, hardening, and keeping production systems trustworthy.

Qualifications

• 6+ years of professional software engineering experience, including meaningful time shipping GenAI/LLM-powered systems in production.
• Real, hands-on depth in agentic AI: reasoning loops, tool/function calling, multi-agent orchestration.
• Practical RAG expertise: chunking strategies, embeddings, vector databases, cosine similarity search, and re-ranking.
• Experience building evaluation and observability for LLM systems: golden datasets, LLM-as-judge, RAGAS or comparable metrics.
• Strong prompt engineering skills — able to write a production system prompt with real structure and constraints.
• Hands-on experience with the AWS GenAI stack: Bedrock, Agent Core, Lambda, DynamoDB, S3, SQS, EventBridge, Step Functions.
• Strong Python and Node.js skills, with experience building full-stack applications and RESTful APIs.
• Solid understanding of production reliability patterns for LLM-backed systems.
• Experience with containerization (Docker) and cloud-native deployment.
• Comfort owning ambiguous, integration-heavy problems.

Helpful Extras and Unique Skills

• Direct experience with Amazon Bedrock Agent Core.
• Experience in a regulated or high-stakes domain (education, healthcare, financial services).
• Familiarity with workflow orchestration tools such as Step Functions, Sequencer, or similar state-machine-based systems.
• A point of view on LLM observability tooling, gained from actually running it in production.

Salary Range

Our salary range is $176,612 - $243,680 CAD.