Staff Software Engineer, Applied AI

HackerOne is a global leader in Continuous Threat Exposure Management (CTEM). The HackerOne 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 pentesting, AI red teaming, and code security, HackerOne delivers measurable, continuous reduction of cyber risk for enterprises. Industry leaders, including Anthropic, Crypto.com, General Motors, Goldman Sachs, Lufthansa, Uber, UK Ministry of Defence, and the U.S. Department of Defense, trust HackerOne to safeguard their digital ecosystems. HackerOne 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).

HackerOne is at a pivotal inflection point in the security industry. Offensive security is no longer optional – it is the standard for forward-thinking companies that want to build trust and resilience in a world where AI-driven innovation and adversaries are moving faster than ever. With the industry shifting, HackerOne stands apart: we combine the ingenuity of the largest security research community with a best-in-class AI-powered platform, trusted by the world’s top organizations.

HackerOne Values

HackerOne is dedicated to fostering a strong and inclusive culture. HackerOne is Customer Obsessed and prioritizes customer outcomes in our decisions and actions. We Default to Disclosure by operating with transparency and integrity, ensuring trust and accountability. Employees, researchers, customers, and partners Win Together by fostering empowerment, inclusion, respect, and accountability.

At HackerOne, we’re advancing a new era of AI-powered offensive security. As a Staff AI Engineer, you’ll help shape the evolution of our autonomous HAI platform, driving the integration of advanced AI and agentic frameworks into HackerOne’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.

At HackerOne, we embrace a Flexible Work approach that gives us the freedom to do our best work while also fostering the connections and community that make us stronger. Reflecting this philosophy, this is a role targeted for candidates within ~50 miles of Seattle, WA or Austin, TX. We believe this balance of proximity and flexibility gives Hackeronies the chance to occasionally come together – fostering collaboration, connection, and in-person moments that enrich our culture – while still preserving the benefits of remote work. Must be able and willing to come to the office once per week on Thursdays.

Success in the Staff AI Engineer role will be accomplished by delivering on the responsibilities below in alignment with the Talent Principles that define how we work at HackerOne.

• 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 HackerOne 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 HackerOne ecosystem. As the company evolves rapidly, bring 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 break problems down and 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, and integrate those learnings into HackerOne’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 HackerOne platform, ensuring security, scalability, and interoperability across systems.

• 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 TensorFlow, 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 AI safety and alignment principles, including responsible AI development, bias mitigation, and ethical AI practices.

• Experience building AI development platforms, model registries, experimentation frameworks, and tools that accelerate AI innovation across organizations.

• Familiarity with ReAct, AutoGen, or Semantic Kernel for agentic orchestration and multi-agent collaboration.

• Experience in agent action routing, secure tool usage APIs, and feedback loops for autonomous agents.

• Knowledge of prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and advanced LLM optimization strategies.

• Experience with cloud-based AI/ML services (AWS Bedrock, GCP Vertex AI, Azure ML) and containerization technologies (Docker, Kubernetes) for AI workloads.

• Familiarity with Ruby on Rails, GraphQL, and React, and experience integrating AI capabilities into production web applications and APIs.

Compensation Bands:

$230K – $280K • Offers Equity

#LI-HM1

• Health (medical, vision, dental), life, and disability insurance*

• Equity stock options

• Retirement plans

• Paid public holidays and unlimited PTO

• Paid maternity and parental leave

• Leaves of absence (including caregiver leave and leave under CO's Healthy Families and Workplaces Act)

• Employee Assistance Program

*Eligibility may differ by country

We're committed to building a global team! For certain roles outside the United States, India, the U.K., and the Netherlands, we partner with Remote.com as our Employer of Record (EOR).

Visa/work permit sponsorship is not available.

Employment at HackerOne is contingent on a background check.

HackerOne is an Equal Opportunity Employer in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, pregnancy, disability or veteran status, or any other protected characteristic as outlined by international, federal, state, or local laws.

This policy applies to all HackerOne employment practices, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. HackerOne makes hiring decisions based solely on qualifications, merit, and business needs at the time.

For US based roles only: Pursuant to the San Francisco Fair Chance Ordinance, all qualified applicants with arrest and conviction records will be considered for the position.