Who we are

Action1 is an autonomous endpoint management platform trusted by many Fortune 500 companies. Cloud-native, infinitely scalable, highly secure, and configurable in 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 (without requiring a VPN), Action1 eliminates routine IT labor, helps prevent ransomware and security risks, and protects the digital employee experience.

In 2025, Action1 was recognized by Inc. 5000 as the fastest-growing private software company in America.

The company is founder-led by Alex Vovk and Mike Walters, entrepreneurs who previously founded Netwrix, a multi-billion-dollar cybersecurity company.

The Role

We are looking for a Applied AI Engineer to build and operate LLM-powered internal solutions, tools, automations, and customer-facing AI features end-to-end.

We are not building AI for the sake of AI, or to follow hype or impress investors. We care about AI that works in real life and solves actual problems.

Technology choices and product decisions are not simply handed down from the top. You will have room to shape the solution, challenge assumptions, choose the right tools, and influence the result.

What you’ll do

Build and operate LLM-powered internal solutions, tools, and automations end-to-end

Ship customer-facing AI features

Drive technical decisions from design through production rollout

Own systems in production, including monitoring, reliability improvements, and incident response participation

Build and maintain LLM evaluation workflows, including quality/safety checks, baselines, and regression detection

Partner with R&D, product, and security teams

Evaluate emerging AI technologies and patterns, and advocate adoption when justified

What we’re looking for

Strong software engineering fundamentals with hands-on ownership of production systems; Python required

Solid LLM application development experience, including context design, structured outputs, and orchestration

Hands-on experience with LLM evaluations, including experiment design, regression detection, gating, and observability

Experience building and operating backend services/APIs in production

Experience designing multi-service architectures and reliable integrations, including stable service contracts, retries, and failure recovery

Working knowledge of operating production databases, including schema design, indexing, migrations, and backup/restore

Hands-on experience with containerized workloads

Ability to balance output quality, latency, and cost in production AI systems

Nice to have

Experience with agentic systems or RAG, including evaluation

Experience building lightweight user interfaces

Experience shipping high-adoption internal developer or operations tooling

JavaScript/TypeScript

AWS deployment and operations experience

Experience with runtime isolation and sandboxing for sensitive execution

Experience in B2B SaaS, security, compliance, or data governance contexts

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.

Applied AI Engineer