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Klue

AI-driven competitive intelligence platform with insights

Senior Software Engineer - AI

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeToronto, ON, Canada

About the Job

Requirements

  • Experience building and operating backend systems in production, with meaningful experience in at least one of search or retrieval, data pipelines, distributed systems, or API-heavy service architectures.
  • Hands-on experience building or significantly improving search, retrieval, or ranking systems, including knowledge of information-retrieval fundamentals such as hybrid retrieval, relevance tuning, and query understanding.
  • Experience building or evaluating agentic or large language model-powered systems, including retrieval-augmented generation, multi-step agent workflows, or similar architectures, and critically evaluating output quality at scale.
  • Strong software engineering fundamentals, including writing clean, maintainable, well-tested code.
  • Comfort with Python and experience with backend frameworks, application programming interfaces, and production infrastructure.
  • Care for reliability, observability, and continuous integration and continuous delivery.
  • Familiarity with vector databases and search infrastructure, such as FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, or OpenSearch, and understanding of their operational tradeoffs.
  • Experience with cloud infrastructure, such as AWS, GCP, or Azure, and building systems that handle scale, large data volumes, low-latency requirements, and high availability.
  • Use of AI coding tools such as Copilot, Cursor, or Claude Code in the development workflow, with ability to discuss their effects on software development.
  • Experience shipping features with understanding of the end-user problem and motivation by customer impact.
  • Ability to lead projects, provide technical direction, own a problem end to end, make architectural decisions, and help others on the team develop.
  • Ability to work through ambiguous problems, learn new areas rapidly, apply scientific rigor alongside pragmatic delivery, and shape unclear requirements into solutions.

Responsibilities

  • Build and ship backend systems that power agentic workflows, including retrieval pipelines, orchestration layers, and multi-step agent architectures that transform competitive data into actionable customer intelligence.
  • Develop and operate automated, offline, and human-in-the-loop evaluation frameworks for agentic systems, measuring relevance, quality, latency, and end-to-end task success, and build infrastructure to measure performance continuously.
  • Design and optimize retrieval and ranking systems across hybrid retrieval, re-ranking, query rewriting, and post-retrieval synthesis so agents surface relevant information at the right time.
  • Improve large language model-powered workflows from prompt design and retrieval strategy through caching and latency optimization to make production agent responses faster, more accurate, and more reliable.
  • Connect technical decisions to customer outcomes by understanding how customers use the product, prioritizing work accordingly, shipping iteratively, measuring impact, and course-correcting.
  • Collaborate with product, infrastructure, and data teams to align technical direction with product goals, contribute to architecture decisions, and establish patterns and best practices for production-grade agentic systems.
  • Evaluate and integrate advances in large language models, retrieval architectures, and agentic reasoning.

Desired Qualifications

  • Experience designing multi-agent systems or complex orchestration workflows.
  • Background in conversational search or dialogue systems.
  • Contributions to open-source projects in search, retrieval, or the large language model ecosystem.
  • Interest in sharing learnings externally through blog posts, talks, or open-source contributions.

About the Company

Klue

AI-driven competitive intelligence platform with insights

Klue is a B2B competitive intelligence platform that combines market, competitor, and buyer insights with AI. It gathers data from millions of sources, surfaces the most relevant intelligence, and stores it in a central hub for easy access, while features like battlecards and newsletters help translate insights into real-time guidance for sales and strategy. It differentiates itself with centralized AI-powered data aggregation plus practical enablement tools and the ability to measure revenue impact and ROI, including improvements in win rates. Its goal is to help businesses win more deals by providing a complete view of the competitive landscape and turning insights into actionable strategies and measurable revenue outcomes.

Company size
51-200
Company stage
Grant
Total funding
$89.5M
Headquarters
Vancouver, Canada
Founded
2015

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