AI Systems Engineer

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Company: Launch Labs

Location: Vancouver, BC V5K 5J9

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!

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