Senior Software Engineer, AI

Klue•Toronto, ON

23d•CA$140,000 - CA$230,000•Hybrid

About The Position

At Klue, we are building the future of competitive intelligence. We are looking for a Senior Software Engineer to join our team in Toronto, focusing on building and optimizing state-of-the-art LLM-powered agents that can reason, plan, and automate workflows for users. You will be leading the design and development of search and retrieval agent systems that enable users to generate competitive insights for their business. In this role, you will own projects end-to-end, guiding architecture decisions, experimentation strategy, and production readiness for LLM-powered retrieval and generation workflows. You will 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.

Requirements

Experience building and operating backend systems in production, with meaningful experience in at least one of: search/retrieval, data pipelines, distributed systems, or API-heavy service architectures.
Hands-on experience with search, retrieval, or ranking systems, including building or significantly improving retrieval pipelines and understanding information retrieval fundamentals.
Experience building or evaluating agentic / LLM-powered systems, including working with retrieval-augmented generation, multi-step agent workflows, or similar architectures and evaluating their output quality at scale.
Strong software engineering fundamentals, including writing clean, maintainable, well-tested code.
Comfort with Python and experience with backend frameworks, APIs, and production infrastructure, with a focus on reliability, observability, and CI/CD.
Familiarity with vector databases and search infrastructure (e.g., FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, or OpenSearch).
Experience with cloud infrastructure (AWS, GCP, or Azure) and building systems that handle scale, large data volumes, low-latency requirements, and high availability.
Experience using AI coding tools (e.g., Copilot, Cursor, Claude Code) to accelerate development.
Customer-oriented mindset, motivated by customer impact.
Ability to lead projects and provide technical direction, make sound architectural decisions, and help others on the team level up.

Nice To Haves

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 LLM ecosystem.
Interest in sharing learnings externally (blog posts, talks, open-source contributions).

Responsibilities

Build and ship backend systems that power agentic workflows, including designing retrieval pipelines, orchestration layers, and multi-step agent architectures.
Own the evaluation of agentic systems at scale by developing and operating evaluation frameworks (automated, offline, and human-in-the-loop) to measure relevance, quality, latency, and end-to-end task success.
Design and optimize retrieval and ranking systems, working across hybrid retrieval, re-ranking, query rewriting, and post-retrieval synthesis.
Improve LLM-powered workflows end to end, from prompt design and retrieval strategy to caching and latency optimization.
Ship features with a customer-centric approach, connecting technical decisions to customer outcomes and prioritizing based on customer usage.
Collaborate across product, infrastructure, and data teams to align technical direction with product goals, contribute to architecture decisions, and establish best practices for production-grade agentic systems.
Stay on the frontier by evaluating and integrating advances in LLMs, retrieval architectures, and agentic reasoning.