Staff AI Engineer

SecurityScorecard is the global leader in cybersecurity ratings, providing organizations with tools to manage and mitigate cybersecurity risks. They are seeking a Staff AI Engineer to lead the design and delivery of AI-powered product initiatives, managing the full software development lifecycle and collaborating with various teams to shape the AI product roadmap.

Responsibilities:

• Lead the design and delivery of major AI-powered product initiatives from concept through production, owning the full software development lifecycle
• Define the technical architecture for AI systems at SecurityScorecard: LLM pipelines, agentic workflows, retrieval infrastructure, and evaluation frameworks
• Set the standard for how the engineering organization builds with AI, including development practices, tooling choices, and quality bars
• Use Cursor, Claude Code, and AI-native development tools as core instruments, and model what high-velocity, high-quality AI-augmented engineering looks like for the team
• Collaborate directly with product leadership and the CTO organization to shape the AI product roadmap
• Drive architecture reviews, establish cross-team engineering standards, and elevate the technical level of the teams you work with
• Identify and eliminate bottlenecks in how AI features get built, tested, and shipped across the organization
• Operate with Staff-level ownership: you see the whole problem, not just your part of it

Requirements:

• 7+ years of software engineering experience with a track record of leading complex, high-impact technical projects end-to-end
• Demonstrated ability to operate independently across the full product development lifecycle, from problem definition through production operations
• 3+ years building and shipping AI-powered product features in production, including LLM integration, agentic systems, or intelligent automation
• Strong product instincts: you think about user problems and business outcomes, not just technical implementation
• Proficiency in TypeScript and strong backend engineering fundamentals with experience in distributed systems at scale
• Fluency with AI-native development workflows (Cursor, Claude Code, or equivalent) as a primary engineering practice, not an experiment
• Cloud infrastructure experience (AWS preferred) and comfort with the full production stack
• Exceptional communication: able to drive alignment across product, engineering, and executive stakeholders
• Prior experience in a Staff or Principal engineering role with cross-team technical influence
• Background in cybersecurity, threat intelligence, or enterprise risk products
• Experience building and operating agentic AI systems, multi-agent orchestration, or LLM evaluation infrastructure
• Track record of defining engineering standards or leading technical strategy at the organizational level
• Experience in high-growth, Series C/D+ companies where engineering velocity and quality both matter