Who we are
Action1 is an autonomous patch management platform trusted by many Fortune 500 companies. Cloud-native, infinitely scalable, highly secure, and configurable in 5 minutes - it just works and is always free for the first 200 endpoints, with no functional limits. By pioneering autonomous OS and third-party patching with peer-to-peer patch distribution and real-time vulnerability assessment and remediation without needing a VPN, it eliminates routine labor, preempts ransomware and security risks, and protects the digital employee experience.
In 2026, Action1 was recognized by Inc. 5000 as the fastest-growing founder-led cybersecurity company in America. At the helm of Action1 are industry veterans Alex Vovk and Mike Walters, American entrepreneurs who founded Netwrix, which has grown into a multi-billion-dollar industry-leading cybersecurity company.
The Role
We are looking for a senior Applied AI Engineer to build practical LLM-powered solutions and implement AI-assisted development best practices
We build AI to solve real problems, not to follow hype or impress investors. You will own technical decisions and delivery, initially focusing on internal tools and workflows, with customer-facing features as a future direction.
What you’ll do
- Own solutions from stakeholder discussions and success criteria through implementation and production support.
- Build reusable coding-agent workflows and help R&D teams adopt them.
- Evaluate and improve AI quality, reliability, latency, and cost.
- Implement technical controls for data access, tool use, and sensitive actions.
What we’re looking for
- Senior-level independence, strong Python skills, and hands-on ownership of production backend services/APIs, with practical database and container experience.
- Professional LLM application experience, including context design, structured outputs, tool calling, and orchestration.
- Experience shipping production software with coding agents such as Claude Code or Codex: designing harnesses and development loops, implementing guardrails, building reusable skills, and managing context, knowledge, and specifications.
- Systematic AI evaluation using datasets, metrics, baselines, reproducible experiments, and regression detection.
- Practical AI security knowledge, including least privilege, sensitive-data protection, and approval controls.
- Sound engineering judgment: choosing solutions based on business value, including deterministic approaches when appropriate.
Nice to have
- Deeper ML foundations, statistical experimentation, and model training or fine-tuning.
- Advanced agent orchestration, RAG, or experience building widely adopted developer tools.
- JavaScript/TypeScript, lightweight UIs, or AWS experience.
- Experience with sandboxing, cybersecurity, B2B SaaS, or data governance.
Technology we use
You do not need to have experience with every tool listed below, but this is the environment we work with now:
- Python, uv, FastAPI, PydanticAI
- PostgreSQL, Docker, Docker Compose
- AWS: EC2, ECR, S3, Lambda
- Interfaces and tooling: Streamlit or similar tools, pytest, ruff, pyright, OpenTelemetry
What We Offer:
- Fully remote work, giving you the flexibility you need in the modern world
- A collaborative environment encouraging you to own your domain and implement best practices
- Stable income, benefits, flexible working hours, and opportunities for promotion.
- Friendly and professional peers, eager to help and help you grow.
- A multitude of interesting challenges and opportunities.