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HackerOne · 1 day ago

Staff Software Applied AI Engineer

Austin, TX

Full-time

Hybrid

Lead/Staff

$230K/yr - $300K/yr

8+ years exp

HackerOne is a global leader in Continuous Threat Exposure Management (CTEM), and they are seeking a Staff Software Applied AI Engineer to drive the integration of advanced AI and agentic frameworks into their products. This role involves building intelligent security agents to help security teams identify, validate, and remediate vulnerabilities more efficiently.

Artificial Intelligence (AI)ComputerCyber SecurityGenerative AIInternetNetwork Security

Culture & Values

No H1B

Hiring Manager

Hannah Meltzer

Responsibilities

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

Qualification

Large Language ModelsGenerative AIMLOps PipelinesAI Platform EngineeringAI Safety PrinciplesCloud-based AI ServicesContainerization TechnologiesChange AgilityData-Driven Decision MakingFirst Principles Problem Solving

Required

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

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