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About The Role

: We are looking for a Senior AI Engineer who ships. This is a hands-on builder role for an engineer who is as comfortable defining the architecture of an agentic workflow as they are reviewing the production code that runs it. You will work at the intersection of LLMs, distributed systems, and real customer problems, turning emerging AI capabilities into features that security teams rely on every day.

What You'Ll Do

Design, build, and ship customer-facing AI-powered product features using TypeScript, Go, and AWS, owning quality and reliability end-to-end Architect and implement agentic workflows, LLM pipelines, and intelligent automation that help customers surface faster, more actionable security insights Integrate foundation models into existing product surfaces with a practical eye toward latency, cost, output quality, and evaluation Use AI-native development tools (Cursor, Claude Code, and similar) as a core part of your workflow, setting the standard for how this team builds Lead architecture and code reviews with a focus on production-grade reliability, security, and maintainability Partner with product and design to translate user needs into compelling AI-driven experiences, contributing product judgment alongside technical execution Own projects end-to-end from concept through production, including monitoring, iteration, and improvement post-launch Stay current with the AI tooling and foundation model landscape and bring relevant advances into our roadmap and practices Required Skills and Experience 5+ years of professional software engineering experience with a strong track record shipping customer-facing product features 2+ years of hands-on experience building AI-powered applications in production, including LLM integration, prompt design, and output evaluation Proficiency in TypeScript and strong backend engineering fundamentals Demonstrated ability to own complex projects end-to-end across the full software development lifecycle Experience designing and operating distributed systems in cloud environments (AWS preferred) Hands-on experience with CI/CD, containerization (Docker, Kubernetes), and production deployment practices Strong computer science fundamentals including systems design, data structures, and networking Fluency with AI-native development workflows including AI-assisted coding tools as part of day-to-day engineering Clear, direct communication with both technical and non-technical stakeholders Our Tech Stack TypeScript / JavaScript, Go, AWS, Docker, Kubernetes, Terraform, ClickHouse, PostgreSQL

Nice To Have

Experience with agentic AI systems, multi-agent orchestration, or retrieval-augmented generation (RAG) Familiarity with LLM evaluation fra