Senior Software Engineer, AI
Klue
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Benefits offered by this job
Job summary
Klue is hiring a Senior Software Engineer in Toronto to build and optimize state-of-the-art LLM-powered agents that reason, plan and automate workflows for users. You will own end-to-end design of search and retrieval pipelines, evaluate agent systems, and push for production-ready, scalable solutions.
You'll collaborate with product, infra, and data teams, ship features with a customer-centric mindset, and help shape architecture decisions while staying ahead of advances in retrieval, LLMs and
Qualifications
- Experience building and operating backend systems in production across search/retrieval, data pipelines, distributed systems, or API-heavy architectures.
- Experience building or evaluating agentic/LLM-powered systems, including retrieval-augmented generation and multi-step workflows.
- Strong software engineering fundamentals: clean, well-tested code, Python, APIs, and production infra; focus on reliability and CI/CD.
Responsibilities
- Build and ship backend systems powering agentic workflows and retrieval pipelines.
- Own evaluation of agentic systems at scale with automated, offline, and human-in-the-loop tests.
- Design and optimize retrieval and ranking systems, balancing BM25, dense retrieval, and hybrids.
- Improve LLM-powered workflows end-to-end, including prompts, caching, and latency optimization.
- Collaborate with product, infra, and data teams to align technical direction with goals.
Skills
Tools
Job description
We’re 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 compete 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.
- Build and ship backend systems that power agentic workflows. You design retrieval pipelines, orchestration layers, and multi-step agent architectures that turn millions of competitive data points (news, press releases, webpage changes, Slack posts, emails, reviews, CRM data) into actionable intelligence for our customers.
- Own evaluation of agentic systems at scale. You develop and operate evaluation frameworks (automated, offline, and human-in-the-loop) that measure relevance, quality, latency, and end-to-end task success across our agent pipelines. You'll define what "good" looks like and build the infrastructure to measure it continuously.
- Design and optimize retrieval and ranking systems. You work across hybrid retrieval, re-ranking, query rewriting, and post-retrieval synthesis to ensure our agents surface the right information at the right time. You understand the tradeoffs between BM25, dense retrieval, and hybrid approaches and know when each matters.
- Improve LLM-powered workflows end to end. From prompt design and retrieval strategy to caching and latency optimization, you'll make our agent responses faster, more accurate, and more reliable in production.
- Ship with the customer in mind. You connect technical decisions to customer outcomes. You're energized by understanding how customers use the product, and you use that context to prioritize what to build next. You ship iteratively, measure impact, and course-correct quickly.
- Collaborate across product, infrastructure, and data teams. align technical direction with product goals, contribute to architecture decisions, and help the team move faster by establishing patterns and best practices for production-grade agentic systems.
- Stay on the frontier. Evaluate and integrate advances in LLMs, retrieval architectures, and agentic reasoning. You have strong opinions (loosely held) about where this space is heading and bring that perspective to your work.
- 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. You've built or significantly improved retrieval pipelines and understand information retrieval fundamentals (hybrid retrieval, relevance tuning, query understanding).
- Experience building or evaluating agentic / LLM-powered systems. You've worked with retrieval-augmented generation, multi-step agent workflows, or similar architectures and have thought critically about how to evaluate their output quality at scale.
- Strong software engineering fundamentals. You write clean, maintainable, well-tested code. You're comfortable with Python and have experience with backend frameworks, APIs, and production infrastructure. You care about reliability, observability, and CI/CD.
- Familiarity with vector databases and search infrastructure. You've worked with tools like FAISS, PGVector, Pinecone, Weaviate, Elasticsearch, or OpenSearch and understand their operational tradeoffs.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and building systems that handle scale, large data volumes, low-latency requirements, and high availability.
- You use AI coding tools to accelerate your own work. You've integrated tools like Copilot, Cursor, Claude Code, or similar into your development workflow and can speak to how they've changed the way you build software.
- Customer-oriented mindset. You've shipped features where you understood the end-user problem, not just the technical specification. You're motivated by customer impact, not just technical elegance.
- Ability to lead projects and provide technical direction. You can own a problem end to end, make sound architectural decisions, and help others on the team level up.
- 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).
We're looking for builders who:
- Take ownership and run with ambiguous problems
- Jump into new areas and rapidly learn what's needed to deliver solutions
- Bring scientific rigor while maintaining a pragmatic delivery focus
- See unclear requirements as an opportunity to shape the solution
- LLM platforms: OpenAI, Anthropic, open-source models
- ML frameworks: PyTorch, Transformers, spaCy
- Search/Vector DBs: Elasticsearch, Pinecone, PostgreSQL
- MLOps tools: Weights & Biases, MLflow, Langfuse
- Infrastructure: Docker, Kubernetes, GCP
- Development: Python, Git, CI/CD
We encourage candidates to apply to the engineering role and level that best align with their experience. To support a fair and consistent review process, candidates are limited to one engineering application every 60 days. Applying to multiple roles will not improve consideration, as our team evaluates candidates holistically across our engineering career framework throughout the interview process.
Not ticking every box? That’s okay. We take potential into consideration. An equivalent combination of education and experience may be accepted in lieu of the specifics listed above. If you know you have what it takes, even if that’s different from what we’ve described, be sure to explain why in your application.
At Klue, we're committed to building a high-performing team where people feel a strong sense of belonging, can be their authentic selves, and are able to reach their full potential. If there’s anything we can do to make our hiring process more accessible or to better support you, please let us know, we’re happy to accommodate.
At Klue, you’ll push the boundaries of what’s possible. For yourself, your team, and our customers. The environment here feels more startup than corporate. You’ll roll up your sleeves, build, iterate, and level up. This is a place where your ideas matter, you can shape what comes next, and leave your mark.
If you’re looking to join a category-defining company… where you own big outcomes, influence real customers, and work with smart, gritty people… you’ll thrive here.
Unlock Your Potential. Take Risks. Take Action. Innovate
We love the balance of connection and flexibility. We work Office-First, with ahybrid touch, and work together in our vibrant offices on Monday, Wednesday & Thursday to collaborate, brainstorm, and build together.
Our main hiring hubs are in:
- Vancouver (HQ)
- Toronto
- London
- High Performance Culture. We reward high performance and growth through career development, coaching, and annual performance reviews.
- Comprehensive benefits: Extended health & dental coverage that starts on Day 1. Fun perks like discounts at Goodlife and Perkopolis are gravy.
- Ownership: All full-time employees have the opportunity to participate in our Employee Stock Option Plan.
- Our Vacation Policy is Take The Time You Need. We just ask that you give notice and don’t leave your team hanging.
- Top-tier tools. All employees will receive a Mac (or PC, if that’s your jam) and access to A+ tooling.
- AI First. All employees are encouraged to lean into AI to work smarter and faster. Built something cool lately? Show us at our Friday Show, Don’t Tell Meetings.
- Growth / Leadership. Direct access to our leadership team, including our CEO, and opportunities to connect with incredible people across the company.
- Social connection. There’s no shortage of ways to stay connected and have fun. We get together once a year in Vancouver for a company- wide kickoff. Throughout the year our Hubs hold regular social events.
- Dog-friendly spaces. Bring your four-legged friend along in Vancouver or Toronto, as our offices are pup-approved.
We’re on a mission to help organizations stop losing winnable deals. Klue’s AI agents generate market, competitor, and buyer insights in a unified platform. We ensure it’s trustworthy, automated, and activated across every department, so they have the answers they need to own their market.
Here’s what makes us tick:
- Klue is AI-first at its core. It’s wired deep into our internal processes and tooling, powering our small but mighty team. It drives Klue’s autonomous agents that handle the heavy lifting for customers: collecting intel, generating insights, and ensuring content is updated and available across departments. Our agents help them scale their impact, stay ahead of the market, and reclaim the time that used to be consumed by manual, repetitive busywork.
- Competitor Insights. Klue helps revenue teams win more competitive deals by turning market, competitor, and buyer signals into insights teams can actually use. Our AI analyzes calls, CRM data, and real buyer feedback to give product marketers and sellers a clear picture of what’s happening in their market and why deals are won or lost. We’re a curious, collaborative team building a platform that helps companies compete with confidence, and we’re looking for people who want to do meaningful work alongside others who care about craft and impact.
- A culture of curiosity, ownership and winning together. We’re a fast-growing, globally-distributed team based in Vancouver (with hubs like Toronto), scaling quicker than ever. We value people who own their domain, act boldly, stay curious and thrive in a collaborative, high-performance environment.
- Klue Blog
- Ignition Acquisition (2025)
- Goldpan.ai Acquisition (2025)
- Win-Loss Acquisition (2023)
- Series A (2020)
- Series B (2021)
- Culture, culture, culture!
- Customer Stories
- Glassdoor
- About Us
- Wellfound (AngelList)
- Product Demo Arena
By submitting your application, you agree that Klue may collect your personal data for recruiting, global organization planning, and related purposes. We may use automated or AI-assisted tools to support our recruitment process. All hiring decisions are made by our hiring team
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