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Klue is building the future of competitive intelligence. We're hiring a Senior Software Engineer to join our Toronto team and lead the design and development of state-of-the-art LLM-powered agents that reason, plan, and automate workflows for users.
In this role, you'll own projects end-to-end, guiding architecture decisions, experimentation strategy, and production readiness for LLM-powered retrieval and generation systems. You'll shape how we integrate retrieval-augmented generation (RAG), dense retrieval, query understanding, and agentic reasoning loops to deliver fast, accurate, and trusted search experiences at scale.
Key responsibilities include:
- Building and shipping backend systems that power agentic workflows, designing retrieval pipelines, orchestration layers, and multi-step agent architectures that transform millions of competitive data points into actionable intelligence
- Owning evaluation of agentic systems at scale, developing automated, offline, and human-in-the-loop evaluation frameworks that measure relevance, quality, latency, and end-to-end task success
- Designing and optimizing retrieval and ranking systems, working across hybrid retrieval, re-ranking, query rewriting, and post-retrieval synthesis
- Improving LLM-powered workflows end-to-end, from prompt design and retrieval strategy to caching and latency optimization
- Shipping with the customer in mind, connecting technical decisions to customer outcomes and iterating based on impact
- Collaborating across product, infrastructure, and data teams to align technical direction with product goals
- Staying on the frontier of LLM, retrieval architecture, and agentic reasoning advances
You bring production backend systems experience with meaningful work in search/retrieval, data pipelines, distributed systems, or API-heavy architectures. You have hands-on experience with search and retrieval systems, understanding information retrieval fundamentals. You've built or evaluated agentic/LLM-powered systems and thought critically about evaluating output quality at scale. Strong software engineering fundamentals with clean, maintainable, well-tested code in Python and backend frameworks. Familiarity with vector databases (FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, OpenSearch) and cloud infrastructure (AWS, GCP, Azure). You use AI coding tools like Copilot or Cursor to accelerate your work. You're customer-oriented, motivated by end-user impact, and can lead projects and provide technical direction.
Tech stack: OpenAI, Anthropic, PyTorch, Transformers, spaCy, Elasticsearch, Pinecone, PostgreSQL, Weights & Biases, MLflow, Langfuse, Docker, Kubernetes, GCP, Python, Git, CI/CD.
