We’re looking for a curious and inventive AI Systems Engineer to help us push the limits of what AI can do for engineering teams. You’ll be joining a small, fast-moving team where ideas turn into shipped features quickly, and where your work will have an immediate impact. You’re someone who loves solving cutting-edge AI challenges, but also knows how to get things into production. You’ll be hands-on with everything from building core application services to tinkering with LLM internals.
About us:
We’re building AI-first tools to make engineering teams faster and smarter. Our mission is to save developers from busywork and give them time to focus on what they’re actually passionate about — building great products & services. From AI-powered summaries and insight generation to spotting blockers before they derail projects, we’re using LLMs and automation to take the friction out of dev workflows.
We’re still early-stage with our AI-powered products and features, so there’s a lot of room to shape where this goes—and a lot of interesting problems left to solve.
What You'll Do
Build and improve dynamic AI pipelines by designing, writing & deploying production Python codeExperiment with various LLM tuning strategies to answer complex qualitative questions (e.g. can AI help identify which tasks are blockers or risks)Boost the quality of AI-generated outputs—whether it’s improving summaries, surfacing insights, or generating new categories from scratchOwn end-to-end features: from scrappy prototype to stable, production-ready deploymentConfigure, maintain and deploy distributed application services to cloud environmentsGet your hands dirty across backend, infrastructure, and AI/ML workflowsIterate fast: tweak prompts, tune models, test outputs, and constantly improveResearch new tools, techniques and frameworks to keep us ahead of the curveAbout You:
You’re AI-savvy, you’ve worked with LLMs and understand how they function under the hoodYou have a builder mindset. You’ve shipped real Python code to production in a team environment and are comfortable with backend frameworks (FastAPI, Flask, etc.)You know how to engineer LLM prompts, validate outputs, and iterate quickly to get high quality resultsYou have experience using Natural Language Processing (NLP) techniques to extract, transform, and parse textual data into meaningful representations suitable for downstream LLM-based operations.You’re used to experimenting and prototyping in NotebooksYou have strong DevOps fundamentals, and experience with CI/CD & cloud services (AWS, GCP, Azure)You have experience with monitoring tooling and troubleshooting production issuesYou’re self-directed, adaptable, and love wearing multiple hats—R&D one day, demoing & debugging your latest pipelines with customers the nextYou can communicate complex technical concepts to non-technical folks (we may ask you to explain how an LLM works under-the-hood)You care about how your work impacts users and drives business valueYou’re always testing new tools or reading up on the latest AI trendsBonus Points
Experience with TensorFlow, PyTorch, or deploying open-source LLMs (Llama, Mistral, etc.) on your own infraKnowledge of graph databases or vector databasesHands-on with serverless (AWS Lambda) or cloud-native tooling (Kubernetes, Docker)An academic or practical background in ML and/or Natural Language Processing (NLP) or computer scienceIdeally based in Vancouver (but we’re open to remote across the Americas)Perks:
Flexible remote work + unlimited vacation (we actually take it)
Annual learning & development budget (conferences, books, courses)
Health & wellness perks
Top-tier gear—whatever you need to do your best work
A no-ego, collaborative team that’s serious about building something great
How to apply:
Send us your resume and/or LinkedIn, plus a link to a project, repo, or anything you’re proud of!
