Senior Software Engineer, Agents

Overview

At Klue, we’re building the future of Competitive Intelligence. Klue Engineering is hiring a Senior Software Engineer in Vancouver to build and optimize state‑of‑the‑art LLM‑powered agents  role is focused on architecture, experimentation, and production readiness for LLM‑powered agents and has a strong customer‑centric impact.

• Build and ship backend systems that power agentic workflows, including retrieval pipelines, orchestration layers, and multi‑step agent architectures that transform millions of competitive data points into actionable intelligence.
• Improve LLM‑powered workflows end‑to‑end, from prompt design and retrieval strategy to caching and latency optimization.
• Own evaluation of agentic systems at scale by developing and operating evaluation frameworks that measure relevance, quality, latency, and task success.
• Design and build human‑in‑the‑loop systems for feedback mechanisms, review workflows, and correction loops.
• Ship with the customer in mind by connecting technical decisions to customer outcomes and iterating based on usage data.
• Collaborate cross‑functionally with product, infrastructure, and data teams to align technical direction with product goals.
• Stay on the frontier of LLMs, retrieval architectures, and agentic reasoning by evaluating and integrating advances.

• Experience building and operating backend systems in production, with significant work in search/retrieval, data pipelines, distributed systems, or API‑heavy service architectures.
• Experience building or evaluating agentic or LLM‑powered systems, including retrieval‑augmented generation and multi‑step agent workflows, and critical evaluation of output quality at scale.
• Strong software engineering fundamentals: clean, maintainable, well‑tested code, proficiency in Python, and experience with backend frameworks, APIs, and production infrastructure.
• Familiarity with search and retrieval systems, including hybrid retrieval, relevance tuning, and query understanding, and tools such as PGVector, Pinecone, or Elasticsearch.
• Experience with cloud infrastructure (AWS, GCP, or Azure) and designing systems that handle large data volumes, low‑latency, and high availability.
• Use of AI coding tools to accelerate development, such as Copilot, Claude Code, or similar, and the ability to discuss their impact.
• Customer‑oriented mindset: shipping features with a clear understanding of user problems and prioritizing user impact.
• Leadership and ownership: ability to own a problem end‑to‑end, make architectural decisions, and mentor teammates.

• Designing multi‑agent systems or complex orchestration workflows.
• Contributions to AI/ML open‑source projects.
• ML fundamentals such as precision, recall, cross‑validation, bias‑variance tradeoff, and regularization.
• Interest in sharing learnings externally through blog posts, talks, or open‑source contributions.

• Owns and drives ambiguous problems with clarity.
• Rapidly learns and delivers solutions in new areas.
• Balances scientific rigor with pragmatic delivery.
• Transforms unclear requirements into well‑defined solutions.

• LLM platforms:
  OpenAI, Anthropic, Gemini
• Agent frameworks:
  PydanticAI
• LLMOps tools:
  Logfire
• Search/Vector DBs:
  Elasticsearch, Pinecone, PostgreSQL
• Infrastructure:
  Docker, Kubernetes, GCP, Temporal
• Development:
  Python, Git, CI/CD

• High Performance Culture with career development and regular reviews.
• Comprehensive benefits: extended health and dental coverage starting on day one, and various perks.
• Ownership: participation in an Employee Stock Option Plan.
• Vacation policy that allows flexible time off.
• Top‑tier tools: a Mac or PC with access to high‑quality tooling.
• AI First mindset: encouragement to incorporate AI to work smarter.
• Growth and Leadership opportunities with direct access to the CEO.
• Strong social connection through events and paid social hires.
• Dog‑friendly spaces in Vancouver and Toronto.