Software Engineer - Research Team

Surf AI is building the world’s first context-driven, agentic security platform. We focus on systems that don’t just surface risk, but actively help organizations resolve it.

Surf is backed by Cyberstarts and Boldstart Ventures, investors behind category-defining security companies, and founded by repeat entrepreneurs with deep experience in identity, security, and enterprise risk.

We’re a small, senior team working at the intersection of security, AI, and distributed systems. Our work blends agentic systems with data-driven analysis and applied security research to operate safely in real enterprise environments.

Who are we looking for?

We're looking for an exceptional Software Engineer to join our Research Team and help us solve the toughest, most complex tasks in the industry.
In this role, you will be the force multiplier for our research efforts.
Your main focus will be enabling our research team to move faster and more effectively. You’ll work directly with researchers  to turn experimental prototypes into reliable software.
This involves automating manual workflows, building internal tools, and guiding code from initial research notebooks into a stable production environment. We’re looking for someone who enjoys the challenge of bringing structure and engineering best practices to a fast-paced research setting.

What you'll do

• Bring research to production: Take experimental code and prototypes (often starting in notebooks) and refactor them into clean, reliable, and maintainable software.
• Tackle the hard engineering problems: Work on the team's toughest technical tasks, such as optimizing complex logic, improving performance, or debugging deep system issues that block progress.
• Automate research workflows: Build internal tools and scripts to handle repetitive tasks - like data processing or model evaluation - so the research team can focus on experimentation.
• Improve system reliability: Help bridge the gap between research and product by ensuring our models are deployed with proper error handling, logging, and stability.
• Support the research lifecycle: Collaborate daily with researchers to understand what they need, fixing infrastructure bottlenecks and ensuring their tools just work.

Qualifications & Skills

• 3+ years of experience in software engineering with a strong focus on backend systems, ML infrastructure, or Python development.
• Production-Grade Python: Mastery of Python with a focus on writing clean, modular, and efficient code. Experience with software best practices (CI/CD, testing, code review) is essential.
• ML Ops & Infrastructure: Experience automating ML workflows. Familiarity with tools like MLflow, Weights & Biases, Ray, or Databricks.
• Cloud & Containerization: Proficiency with Docker and Kubernetes. Experience deploying and scaling jobs on cloud platforms (AWS, GCP, or Azure).
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related technical field, or equivalent practical experience or training.

Bonus Experience

• A background in building internal developer platforms or research labs.
• Curiosity and a drive to understand the "why" behind the models, not just the "how."
• Deep Learning Ecosystem: solid understanding of PyTorch and the Hugging Face ecosystem. You don't need to be a researcher, but you need to speak their language.
• Data Handling: Experience handling large datasets and integrating with graph DB  to support research initiatives.

Why Join Us?
If you want to work on foundational systems, ship AI into production, and help define how agentic security actually operates, this is an opportunity to do it early and with real ownership.