We're looking for a Software Engineer, AI 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'll be joining us at an exciting time as we reinvent our insight generation systems, making this an excellent opportunity for someone with strong Backend and ML fundamentals who wants to dive deep into practical LLM applications.
As a member of our team, you'll be leading the design and implementation of search and retrieval agent systems that enable users to discover high-quality, relevant information with minimal effort. You will work at the intersection of LLM-powered agent workflows, retrieval pipelines, and evaluation frameworks, ensuring that our systems remain scalable, efficient, and aligned with user intent.
Design and implement retrieval-augmented generation (RAG) systems with agentic workflows to refine query understanding, document retrieval, and response synthesis.
Build and optimize retrieval pipelines using BM25, dense retrieval, hybrid retrieval, and re-ranking approaches.
Develop evaluation pipelines for retrieval and generation, including offline metrics (recall, MRR, nDCG) and human-in-the-loop evaluations.
Experiment with query rewriting, expansion, and classification to improve retrieval relevance.
Collaborate closely with Product to bring ML-powered search agents into production.
Profile, debug, and optimize the latency, accuracy, and scalability of retrieval and generation components.
Contribute to the design of data pipelines for training retrieval and ranking models, including dataset curation, augmentation, and labeling workflows.
Stay up-to-date with advancements in LLMs, retrieval techniques, and agent architectures, evaluating opportunities to integrate them into our systems.
Software engineering experience
Experience with information retrieval systems, search relevance, and ranking models
Expertise in Python, with experience in frameworks such as PyTorch, TensorFlow, or JAX.
Familiarity with LLMs, prompt engineering, and retrieval-augmented generation pipelines.
Understanding of evaluation methods for search systems, including offline metrics and user-facing evaluation.
Experience working with vector database infrastructure (FAISS, Milvus, Weaviate, Pinecone, PGVector) and traditional search engines (Elasticsearch, OpenSearch)
Understanding of data pipelines, preprocessing, and large-scale data handling.
Ability to work independently and collaboratively in a fast-paced environment, balancing research and production needs.
Develop and implement CI/CD pipelines. Automate the deployment and monitoring of ML models.
Knowledge of query understanding, document summarization and other content enrichment strategies
Expertise in automated LLM evaluation, including LLM-as-judge methodologies
Skilled at prompt engineering - including zero-shot, few-shot, and chain-of-thought.
Experience with cloud infrastructure (AWS, GCP, Azure) for scalable ML workflows.
Nice to Have
Experience with agentic system design for LLM workflows.
Background in conversational search.
Contributions to open-source projects in the retrieval, NLP, or LLM ecosystems.
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
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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 Mondays, Wednesdays & Thursdays 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.
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