Senior Software Engineer, Agents

GuruLink; Vancouver; On-site; CAD 120,000 - 180,000; Full time

Job summary

GuruLink in Vancouver, BC is seeking a Senior Software Engineer to design and optimize LLM-powered agents at scale, spanning multi-agent orchestration and evaluation frameworks.

You will own projects end-to-end — architecture, experimentation strategy, and production readiness — while optimizing inference cost, retrieval performance, and feedback loops that help agents improve over time. You’ll also influence the roadmap with a technical perspective alongside product leadership.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Backend systems

LLM/agent systems

Python

Vector databases

Cloud infrastructure

AI coding tools

Deliver business outcomes

End-to-end ownership

Tools

PGVector

Pinecone

Elasticsearch

Job description

Location: Vancouver, British Columbia

About the company:

Our client is a fast-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.