[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![HackerOne logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/8937d355-221.png)](https://jobicy.com/company/hackerone.md)Remote opportunity at[HackerOne](https://jobicy.com/company/hackerone.md) # Senior Manager, AI Engineering Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/hackerone.md)Share4 Sep 2026Published45Listing views4Application actions4 Oct 2026Apply before Opportunity details ## About this role. AI SummaryThis senior engineering leadership role manages multiple AI engineering teams building production AI capabilities for an offensive-security platform. The leader will develop Engineering Managers and senior engineers while owning execution, cross-team dependencies, delivery reliability, and customer-facing outcomes. The position requires strong applied AI and modern software-systems judgment, with close partnership across Product, Design, Data, and Security Research. It is a remote role for candidates located within roughly 50 miles of Seattle, Washington, or Austin, Texas, with weekly office attendance expected. The work emphasizes responsible AI, agentic and human-in-the-loop workflows, data-driven operations, and scalable engineering practices. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThe role combines senior people leadership across multiple teams with technical accountability for applied AI systems in a security-sensitive product environment. Success requires navigating rapidly evolving AI technology, complex dependencies, operational reliability, and high-stakes cross-functional decisions. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianHighly competitive$260,000US market range$220k–$300k0$330k AI insightThe disclosed yearly base-salary range is USD 240,000 to USD 280,000, yielding a midpoint of USD 260,000. For a US-based Senior Manager of AI Engineering, an estimated market base-salary range is USD 220,000 to USD 300,000; total compensation may be higher with the stated equity options, which are not included in the base-pay figures. ## Core skills Skills and capabilities most closely associated with this opportunity. [AI engineering leadership](https://jobicy.com/jobs?search_keywords=AI%20engineering%20leadership.md)[Applied AI systems](https://jobicy.com/jobs?search_keywords=Applied%20AI%20systems.md)[Engineering management](https://jobicy.com/jobs?search_keywords=Engineering%20management.md)[People development](https://jobicy.com/jobs?search_keywords=People%20development.md)[Agentic AI](https://jobicy.com/jobs?search_keywords=Agentic%20AI.md)[Responsible AI](https://jobicy.com/jobs?search_keywords=Responsible%20AI.md)[Cybersecurity](https://jobicy.com/jobs?search_keywords=Cybersecurity.md)[Software architecture](https://jobicy.com/jobs?search_keywords=Software%20architecture.md)[Cross-functional leadership](https://jobicy.com/jobs?search_keywords=Cross-functional%20leadership.md)[Data-driven decision-making](https://jobicy.com/jobs?search_keywords=Data-driven%20decision-making.md) Sample interview questionsHow have you led multiple engineering teams delivering AI-powered products with shared dependencies?I establish clear product outcomes, assign accountable owners for each dependency, and use a regular operating cadence to review delivery risk, system health, and decisions. I empower managers to own execution while escalating only issues that require organizational trade-offs or executive alignment. How do you evaluate whether an applied AI capability is ready for production? I define measurable quality, reliability, latency, safety, and customer-value criteria before launch. I use staged releases, monitoring, evaluation datasets, human review where appropriate, and rollback plans so that model behavior can be continuously assessed and improved. What is your approach to developing Engineering Managers? I set explicit expectations around people leadership, execution, technical judgment, and stakeholder management, then provide frequent coaching tied to real decisions and outcomes. I also create opportunities for managers to lead cross-team initiatives, supported by actionable feedback and measurable growth goals. How would you implement responsible AI practices in a security product? I would embed security, privacy, evaluation, auditability, and human-oversight requirements into product development rather than treating them as a final review. This includes threat modeling AI workflows, monitoring for unsafe or unreliable outputs, maintaining clear decision records, and partnering closely with security researchers. How do you maintain delivery momentum when AI technology and priorities change quickly? I separate durable customer problems from implementation choices, maintain a prioritized roadmap, and run short learning cycles to validate technical assumptions. I communicate trade-offs transparently, protect team focus, and re-plan deliberately when evidence shows a different approach will create more customer value. 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](http://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. ### Senior Manager, AI Engineering ### Remote Location: Seattle, WA or Austin, TX ### Position Summary At HackerOne, AI is central to how we help organizations continuously identify and reduce cyber risk. As a Senior Manager, AI Engineering, you will lead multiple AI engineering teams building and scaling AI-powered capabilities across our offensive security platform. Your work will directly impact how customers discover vulnerabilities earlier, remediate faster, and trust AI-driven security outcomes at scale. In this role, you will empower Engineering Managers and senior engineers, shape how applied AI is delivered responsibly, and ensure teams consistently translate AI innovation into reliable, customer-impacting products. You will partner closely with Product, Design, Data, and Security Research to scale AI systems that combine automation with human expertise in meaningful ways. 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 remote role targeted for candidates within ~50 miles of Seattle or Austin. 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. NOTE: Must be able and willing to come to the office once per week (typically Thursdays). ### What You Will Do Success in the Senior Manager, AI Engineering role will be accomplished by delivering on the responsibilities below in alignment with the Values and Principles that define how we work at HackerOne. * Multiply Your Impact by leading, mentoring, and developing Engineering Managers and senior engineers, building scalable systems and practices that allow teams to deliver AI-powered solutions consistently and independently * Own the Outcome for execution across multiple AI engineering teams, ensuring delivery commitments are met, dependencies are actively managed, and teams are accountable for customer-visible impact * Drive an AI First approach to engineering by embedding AI-powered workflows, agentic systems, and responsible AI practices into how teams design, build, and operate products * Practice Change Agility by guiding teams through evolving AI technologies, shifting priorities, and emerging security threats while maintaining clarity, momentum, and team health * Apply First Principles Problem Solving to complex AI and product challenges, breaking problems down to fundamentals and designing durable, scalable solutions rather than short-term workarounds * Leverage Data-Driven Decision Making to assess system performance, model quality, delivery outcomes, and operational health, using evidence to inform priorities and improvements * Collaborate cross-functionally with Product, Design, Data, Security Research, and other Engineering leaders to align AI engineering efforts with company strategy and customer needs ### Minimum Qualifications * 5+ years of experience managing product engineering teams, including teams delivering AI-powered or data-intensive systems * Demonstrated experience leading teams with complex dependencies across engineering, product, and non-technical partners * Experience developing and mentoring Engineering Managers * Strong technical foundation in modern software systems that support AI-enabled products ### Preferred Qualifications * Experience building or scaling applied AI systems in production environments * Familiarity with human-in-the-loop, agentic, or automation-driven workflows * Experience with technologies in HackerOne’s core stack, including PostgreSQL, Rails, GraphQL, Apollo, and React ### Compensation Bands * Base salary: $240,000 to $280,000 * Offers equity (stock options) #LI-MH1 ### Job Benefits: * 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](https://remote.com/preemployment-faq) 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. 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