Job description
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 code
- Experiment 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 scratch
- Own end-to-end features: from scrappy prototype to stable, production-ready deployment
- Configure, maintain and deploy distributed application services to cloud environments
- Get your hands dirty across backend, infrastructure, and AI/ML workflows
- Iterate fast: tweak prompts, tune models, test outputs, and constantly improve
- Research new tools, techniques and frameworks to keep us ahead of the curve
About You:
- You’re AI-savvy, you’ve worked with LLMs and understand how they function under the hood
- You 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 results
- You 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 Notebooks
- You have strong DevOps fundamentals, and experience with CI/CD & cloud services (AWS, GCP, Azure)
- You have experience with monitoring tooling and troubleshooting production issues
- You’re self-directed, adaptable, and love wearing multiple hats—R&D one day, demoing & debugging your latest pipelines with customers the next
- You 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 value
- You’re always testing new tools or reading up on the latest AI trends
Bonus Points
- Experience with TensorFlow, PyTorch, or deploying open-source LLMs (Llama, Mistral, etc.) on your own infra
- Knowledge of graph databases or vector databases
- Hands-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 science
- Ideally 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!
