Software Applied AI Engineer

Join to apply for the Staff Software Applied AI Engineer role at Hacker One
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Hacker One is a global leader in Continuous Threat Exposure Management (CTEM). The Hacker One Platform unites agentic AI solutions with the ingenuity of the world’s largest community of security researchers to continuously discover, validate, prioritize, and remediate exposures across code, cloud, and AI systems. Through solutions like bug bounty, vulnerability disclosure, agentic pen testing, AI red teaming, and code security, Hacker One delivers a measurable, continuous reduction of cyber risk for enterprises.

Industry leaders, including Anthropic, , General Motors, Goldman Sachs, Lufthansa, Uber, UK Ministry of Defence, and the U.S. Department of Defense, trust Hacker One to safeguard their digital ecosystems. Hacker One was recognized in Gartner’s Emerging Tech Impact Radar: AI Cybersecurity Ecosystem report for its leadership in AI Security Testing and has been named a Most Loved Workplace for Young Professionals (2024).

Seattle, WA or Austin, TX (must be within ~50 miles of the location, willing to travel to the office once per week, typically Thursdays).

As a Staff AI Engineer
, you’ll help shape the evolution of our autonomous HCl platform, driving the integration of advanced AI and agentic frameworks into Hacker One’s products. You will build intelligent security agents that reason, act, and learn—helping security teams identify, validate, and remediate vulnerabilities faster than ever. This is a high‑impact technical role, reporting to the VP, AI Engineering, where you will architect the systems and frameworks that power the next generation of AI‑driven vulnerability discovery.

• Architect and enhance our autonomous security agent "Hai," building intelligent systems capable of natural‑language reasoning, vulnerability detection, and actionable recommendations, all grounded in an AI‑first mindset.
• Build components and services that integrate agentic AI design patterns—such as orchestration, memory systems, RAG, long‑horizon tasks, and LLM‑based models—into the Hacker One platform, applying an AI‑first approach to improve vulnerability detection and security automation.
• Partner across Product, Security Research, and Engineering to introduce AI capabilities into the broader Hacker One ecosystem, bringing clarity and stability to shifting requirements by demonstrating strong change agility.
• Design and implement AI red‑teaming agents and frameworks that proactively surface weaknesses in LLMs, generative‑AI systems, and applied AI deployments, using first‑principles problem solving to build durable, foundational solutions.
• Establish meaningful metrics, observability, evaluation frameworks, and continuous feedback loops to improve model performance, safety, and user impact—ensuring decisions are grounded in data‑driven decision making.
• Stay current with emerging AI safety research, adversarial‑testing techniques, and agentic‑system patterns, integrating those learnings into Hacker One’s responsible‑AI strategy with adaptability and a growth‑oriented change‑agility mindset.
• Build APIs and integrations that enable seamless interaction between AI models, security tools, and the broader Hacker One platform, ensuring security, scalability, and interoperability across systems.
• Must be able and willing to come to the office once per week (typically Thursdays).

• 8+ years of experience as a software engineer, including deep experience building and maintaining production‑grade AI platforms and infrastructure.
• Must be able and willing to come to the office once per week (typically Thursdays).
• Proven expertise in large language models (LLMs), generative AI, and machine learning frameworks such as Tensor Flow, PyTorch, and Transformers in production environments.
• Strong hands‑on experience in AI platform engineering, including model deployment, MLOps pipelines, model serving infrastructure, and shared AI services architecture.
• Experience building systems that support multiple AI product teams and applications, enabling scalable experimentation and deployment.
• Solid understanding of…