Location: Vancouver, British Columbia

About the company:
Our client is a rapid-growing, venture-backed B2B SaaS company building an AI-powered competitive intelligence platform that helps revenue teams win more competitive deals. The company is AI-first internally, and its product is trained in part on proprietary data unavailable anywhere else on the open web.

About the role:
We're hiring a Senior Software Engineer to build and optimize state-of-the‑art LLM-powered agents at scale, spanning multi-agent orchestration, sub-agent design, and the evaluation frameworks that keep outputs trusted and measurable. You'll own projects end-to-end — architecture, experimentation strategy, and production readiness — while optimizing inference cost, retrieval and query performance, and the feedback loops that help agents improve over time. You'll also help shape the roadmap itself, bringing a technical point of view and working closely with product leadership.

What you'll do:

Build backend systems for agentic workflows — retrieval pipelines, orchestration layers, and multi-step agent architectures.

Own evaluation of agentic systems at scale — build and operate frameworks measuring relevance, quality, latency, and task success.

Design human-in-the-loop systems — feedback mechanisms, review workflows,



and correction loops that keep agents accurate over time.

Optimize LLM workflows end to end — prompt design, retrieval strategy, caching, and latency.

Collaborate across product, infrastructure, and data teams to shape technical direction and roadmap.

Must Have Skills:

Production experience with backend systems — search/retrieval, data pipelines, distributed systems, or API-heavy services.

Experience building and/or evaluating agentic or LLM-powered systems (RAG, multi-step agents).

Strong Python and software engineering fundamentals (testing, CI/CD, observability).

Experience with retrieval/search systems and vector databases (PGVector, Pinecone, or Elasticsearch).

Experience with cloud infrastructure at scale (AWS, GCP, or Azure).

Regular use of AI coding tools (Copilot, Cursor, Claude Code, or similar).

Track record of shipping features tied to real user/business outcomes.

Ability to own a project end-to-end and provide technical direction.

Nice to Have Skills:

Multi-agent systems or complex orchestration design.

ML fundamentals (precision/recall, cross-validation, bias-variance tradeoff, overfitting/regularization).

Open-source contributions in AI/ML.

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📌 Senior Software Engineer, Agents (British Columbia)
🏢 GuruLink
📍 British Columbia