Senior Full Stack AI Engineer

OmbudQuinte West, ON
Hybrid

About The Position

We're hiring two senior full-stack engineers to build the next generation of Ombud's agentic AI platform. The work splits across two domains: building the agentic engine itself (LlamaIndex / agent orchestration / tool calling / evaluation pipelines) and the ML data engineering that supports it (embeddings, vector store operations, retrieval quality, RAG/CAG architectures). These are high-output IC roles. You will ship production code, own systems end-to-end, and operate without a layer of engineering management between you and the product direction. You will work directly with the CEO on architectural decisions and directly with the platform engineer on production deployment. We are not hiring engineering managers and we are not hiring junior engineers.

Requirements

  • 6+ years of professional full-stack software engineering experience, with demonstrated production system ownership.
  • Deep Python fluency.
  • JavaScript / TypeScript / React competence.
  • Hands-on production experience integrating LLMs into product (Anthropic, OpenAI, Google).
  • Working knowledge of RAG architectures, embeddings, vector databases, and the trade-offs between retrieval and context-caching approaches.
  • Fluency with Claude Code or similar AI-augmented development workflows.
  • Strong intuition for system design: can take a vague product goal, design the architecture, and ship the implementation without needing intermediate hand-holding.
  • Comfort operating in a small team without a layer of engineering management. You bring problems with proposed solutions, not just problems.
  • Willingness to be in-office Tuesday through Thursday in Denver.

Nice To Haves

  • Production experience with LlamaIndex, LangChain, LangGraph, or similar agent orchestration frameworks.
  • Experience designing and operating evaluation pipelines for LLM applications (Langfuse, Braintrust, or custom).
  • Vector database operations at scale (Qdrant, Pinecone, Weaviate).
  • Browser extension or Office add-in development (Chrome extensions, Office365 / Excel add-ins).
  • Open source contributions, particularly in the AI tooling ecosystem.
  • Prior experience in revenue operations, sales enablement, or response management software.

Responsibilities

  • Build the agentic engine (LlamaIndex / agent orchestration / tool calling / evaluation pipelines).
  • Develop ML data engineering for embeddings, vector store operations, retrieval quality, and RAG/CAG architectures.
  • Own Ombuddy Native: our next-generation agentic platform replacing the existing Chrome extension, including production agent orchestration, tool design, and multi-step reasoning workflows.
  • Develop RAG and CAG architecture: embeddings, retrieval, re-ranking, caching strategies.
  • Integrate LLMs with Anthropic Claude (primary), with multi-model routing.
  • Build evaluation pipelines to measure response quality, regression-test prompts, and ship LLM-dependent features with confidence.
  • Develop self-service infrastructure: customer onboarding flows, content ingestion automation, in-product setup experiences.
  • Deliver full-stack features across Python (primary backend), Node.js (legacy services), React (frontend), PostgreSQL, and Elasticsearch.
  • Own features through production operations: deployment, monitoring, and customer-facing incidents.
  • Conduct code review and provide technical mentorship within a small, senior engineering team.

Benefits

  • Work directly with the CEO on architectural decisions.
  • Work directly with the platform engineer on production deployment.
  • Operate without a layer of engineering management.
  • Ship production code.
  • Own systems end-to-end.
  • Use AI as a force multiplier on your own output.
  • Be on-call rotation capable (within 60 days).
  • Drive a substantive piece of the Ombuddy Native or self-service roadmap (within 90 days).
  • Establish yourself as a trusted technical voice on architectural decisions (within 90 days).
  • Ship measurable improvements to either response quality, system performance, or developer velocity (within 90 days).
  • Work in an environment where AI fluency translates directly to product impact.
  • Deploy frequently, ship real customer value.
  • Trust engineers to operate as senior partners.
  • Work on the actual product behind the agentic enterprise era.
  • Use Claude as a teammate, not a feature checkbox.
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