HackerOne Inc.
Staff Software Applied AI Engineer
Location: Seattle, WA
Position Summary
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 . Must be able and willing to come to the office once per week (typically Thursdays).
What You Will Do 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 .
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.
Minimum Qualifications
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 .
Preferred Qualifications
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 Seattle
$230K – $300K • Offers Equity
#LI-Remote
#LI-HM1
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
Flexible Work Stipend
*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.
#J-18808-Ljbffr
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 . Must be able and willing to come to the office once per week (typically Thursdays).
What You Will Do 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 .
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.
Minimum Qualifications
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 .
Preferred Qualifications
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 Seattle
$230K – $300K • Offers Equity
#LI-Remote
#LI-HM1
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
Flexible Work Stipend
*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.
#J-18808-Ljbffr