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# Staff Software Engineer, Applied AI

- **Company:** Hackerone Inc.
- **Location:** Washington, DC, United States
- **Experience:** Expert
- **Salary:** $230,000.0 - $280,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Decision Support Systems, Software Design Patterns, Interoperability, Machine Learning, Software Product Management, Ruby on Rails, Tensorflow, Azure Machine Learning, Software Safety, Systems Integration, Web Applications, Pytorch, ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Google Vertex AI, Generative AI, Containerization, AI Platforms, Kubernetes, AutoGen, Graphql, Machine Learning Operations, Semantic Kernel, Docker, Security Orchestration, Automation & Response, Vulnerability Analysis
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_1bbc1f7d635a965463ab4ddae6ed7892

## About the Role

* 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.

## Description

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., * 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, demonstrating strong Change Agility in a rapidly evolving environment.
 * 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 HackerOne's responsible-AI strategy with 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.