Applied AI Engineer

Action1 is an autonomous patch management platform trusted by many Fortune 500 companies. It is cloud-native, infinitely scalable, highly secure, and configurable in 5 minutes. The platform pioneers autonomous OS and third-party patching with peer-to-peer patch distribution and real-time vulnerability assessment without needing a VPN, eliminating routine labor and preempting ransomware and security risks. Action1 was recognized by Inc. 5000 as the fastest-growing founder-led cybersecurity company in America. The company was founded by industry veterans Alex Vovk and Mike Walters, also founders of Netwrix.

• 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

• 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