Senior Applied AI Engineer
About The Position
AI is moving faster than any single product team can keep up with. For a security company, the hard question isn’t “can a model do this?” It’s which approach actually works, what it costs, how fast and reliable it is, and whether it’s worth building at all. That’s what this team answers. We’re an Applied AI Research team, and research is our product. We take important questions the company can’t yet answer and turn them into evidence people can act on. As a Senior/Staff Applied AI Engineer, you’ll own a line of research from start to finish: frame the question, build what’s needed to answer it, measure honestly, and reach a decision. When something is ready to move to another team, you’ll help them deploy it well, advising on the AI side and on how to monitor it once it’s live. Sometimes the answer is “this works, here’s the proof.” Sometimes it’s “this won’t work, and we found out in three weeks instead of six months.” Both count as success here.
Requirements
- 5+ years building software and ML systems, with recent hands-on work on LLM systems that went past the prototype stage.
- Experience building agents that do real work, and you’ve dealt with what goes wrong when they run for a long time.
- Experience with third-party model APIs and open-weight models (we run on our own GPU fleet)
- Experience with Kubernetes inference platform, Flyte for orchestration, LiteLLM / Langfuse and internal tooling for evaluation and tracing.
- Experience building evals that gave you a real answer, and you know how easily they can mislead.
- Experience getting strong results out of frontier models, hosted or self-hosted.
- Strong Python and solid ML fundamentals.
- Experience with Claude Code, Cursor or similar, used daily, without lowering your standard for correctness and tests.
Nice To Haves
- Experience fine-tuning or serving open-weight models
- Experience with automated prompt and pipeline optimization
- Experience with multi-GPU serving and or MCP and tool protocols
- Previous cybersecurity experience such as phishing or threat detection
- Open-source contributions or publications.
Responsibilities
- Answer hard questions with evidence. Take a question nobody has answered yet. Make it testable, set a baseline, run the smallest experiment that settles it, and come back with an answer the company can act on.
- Build systems that improve themselves. A lot of our agentic work runs in long loops: run an evaluation, study the results, produce a better version, run it again. You’ll build systems that improve on their own and recover when they go wrong.
- Make agent behaviour measurable. Extend our evaluation platform so we can tell whether an agent is genuinely good - task suites, regression checks, and honest tradeoffs between quality, cost and speed. It’s something we build and maintain for the whole company.
- Work across hosted and self-hosted models. Most of what we do runs on third-party model APIs. We also serve open-weight models on our own GPUs and are pushing further into fine-tuning and efficient serving. You’ll help us work out which jobs suit which.
- Improve how we build with coding agents. We use coding agents every day and benchmark them against our own codebases. You’ll help our engineers get more out of them.
- Start from real problems. Spend time with stakeholders, understand their problems rather than collecting feature requests, and turn what you hear into research worth doing.
- Put working things in people’s hands. Build prototypes, playgrounds and APIs so stakeholders can try an idea themselves and learn alongside us. Often that’s how the decision gets made.
- Help get it into production. When something works, we don’t just hand it over. You’ll advise the team deploying it - on the AI side, and on how to monitor and understand the system once it’s running.
- Help the team get better. Mentor engineers, share what you learn, and help the team ask better questions.
Benefits
- Competitive compensation
- Comprehensive benefits
- Career success on your terms
- Flexible work environment
- Annual wellness and community outreach days
- Always on recognition for your contributions
- Global collaboration and networking opportunities
- flexible time off
- comprehensive well-being program with two paid Wellbeing Days and two paid Volunteer Days per year
- three-week Work from Anywhere option
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
