Design, build, and evolve the MDASH scanning engine, integrating AI agents and models to analyze codebases, detect vulnerabilities, and generate fixes.
Locations (3)
Redmond, Washington, United States
San Francisco, California, United States
New York, New York, United States
Compensation
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Responsibilities
Design, build, and evolve the MDASH scanning engine, including agent orchestration, multi-model routing, code understanding, vulnerability detection, reachability validation, and fix generation and verification.
Extend the engine's coverage across vulnerability classes, programming languages, frameworks, build systems, and codebase sizes, from single services to large monorepos.
Integrate program analysis techniques into agent workflows to make detections more precise and grounded.
Improve the engine's precision, recall, consistency, and fix quality, working from evaluation results, research findings, and production feedback.
Optimize scan performance, scalability, cost, and latency so MDASH works well on enterprise-scale codebases and in CI/CD workflows.
Requirements
Bachelor's Degree in Computer Science or related technical field
Master's Degree in Computer Science or related technical field
Nice to have: Master's Degree in Computer Science or related technical field
Nice to have: 8+ years technical engineering experience
Nice to have: 12+ years technical engineering experience
Lead a new product engineering team focused on developing AI agent products for cybersecurity use cases, balancing hands‑on engineering with people management.
Responsibilities
Build and lead a new high‑performance team
Define team structure and operating model
Coach engineers on technical excellence and secure development
Contribute to product architecture and system design
Review and approve technical designs and security‑sensitive implementations
Requirements
Advanced degree in Computer Science or related fields
Nice to have: experience building or leading cybersecurity products
Lead the design, build, and deployment of AI‑native solutions for enterprise customers, acting as the technical CTO of the build and delivering production‑grade GenAI/ML systems.
Responsibilities
Partner with customers to discover problems and frame high‑impact AI use cases
Design and build end‑to‑end GenAI/ML systems—RAG pipelines, agentic workflows, evaluation, and guardrails
Prototype quickly, iterate with real users, and harden pilots into reliable, monitored services
Own the technical relationship, translating between business stakeholders and engineering
Raise the bar for ML depth and engineering quality across the team
Requirements
Nice to have: Integrating AI into SaaS platforms like ServiceNow or Salesforce
Nice to have: Track record of production deployments in secure, regulated enterprise environments
Nice to have: Contributions to dev experience tooling, frameworks, or reusable AI scaffolds
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