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# Distinguished Software Engineer, AI

- **Company:** SecurityScorecard
- **Location:** United States
- **Experience:** Expert
- **Salary:** $350,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Mobile Application Development, Code Review, Continuous Integration, Cursor, Distributed Systems, Software Deployment, TypeScript, Cloud Platform System, Large Language Models, Claude Code, AI Coding Agents, Containerization, Kubernetes, Information Technology, Low Latency, Codebase, Docker, Golang
- **Published:** October 27, 2026
- **Apply:** https://job-boards.greenhouse.io/securityscorecard/jobs/8324966

## About the Role

* 10+ years building and shipping production software, with a track record at strong engineering companies (big tech, high-growth startups, or both)
 * Evidence that you drove things. We want the people who set the direction on their teams, not the ones who rode along.
 * Deep computer science and system design fundamentals. You can design a distributed system on a whiteboard and explain how it fails.
 * Heavy, hands-on use of AI coding tools on real codebases, with opinions about what works and what doesn't
 * Experience building with LLMs: agents, tool use, evals, prompt, and context design
 * Proficiency in TypeScript and strong backend engineering fundamentals
 * Comfort with ambiguity and a team that changes shape. You'll help define the job as we go.
 * Experience designing and operating distributed systems in cloud environments (AWS preferred)
 * Hands-on experience with CI/CD, containerization (Docker, Kubernetes), and production deployment practices
 * Clear, direct communication with both technical and non-technical stakeholders

## Description

* Design systems that stay sound when most of the code is written by agents, and decide where humans need to stay in the loop
 * Ship real changes to our products, using them as test cases for the new way of working
 * Pair with engineers across the org, review their work and help them adopt what we learn
 * Raise the hiring bar: interview candidates and help decide who joins the team
 * Write down what we learn so other teams can use it without us in the room
 * 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 (Claude Code, Codex, Cursor, etc.) 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
 * 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, Expect a system design round, a coding exercise where you're expected to use AI tools, and a deep dive into a project you led, including how you used AI on it. We'll ask follow-up questions until we understand the decisions you made and why.