Distinguished Software Engineer, AI

About SecurityScorecard:

SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix

cybersecurity risks across their digital footprint.

Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.”  SecurityScorecard is proud

to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital.

About the Role:

We're starting a new engineering team, and its job is to change how SecurityScorecard builds software. You'll be one of the first people on it.

The team works out how a company our size should ship code now that agents can write most of it. That means real work on the codebase: running agentic coding workflows end to end, finding where they break, building the tooling and guardrails that fix those breaks, and turning what works into the way the rest of engineering operates. We'll pick product areas to test against as we go. Over time the team takes on real product ownership and folds back into the wider engineering org.

We want strong engineers who went deep on AI coding because they couldn't leave it alone. You know how production systems fail and you've pushed agentic tools far enough to know where they still fall short. You also care about building a team you'd want to work on, and you'll stick around after the novelty wears off.

This is greenfield. You'll report to our CTO or to an engineer leading the team, and the reporting lines will move as the team grows. If titles and org charts matter a lot to you, this role won't be a good fit. We care about execution and impact.

What you'll do

• Run agentic coding workflows on production code and find out what actually holds up at our scale
• Build the tooling, guardrails, evals and review practices that let agents ship code we trust
• 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
• Required Qualifications: 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
• Our tech stack
• TypeScript / JavaScript, Go, AWS, Docker, Kubernetes, Terraform, ClickHouse, PostgreSQL
• How we interview: 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.
• Location and compensation: Remote. We're hiring across United States, Canada, and Latin America.