Senior Software Engineer, Applied AI

What You Will Do

Success in this role will be accomplished by delivering the responsibilities below in alignment with HackerOne’s Talent Principles: AI-First, Change Agility, Data-Driven Decision Making, and First Principles Problem Solving.

• Contribute to evolving our AI security agent Hai, implementing features that enable natural language security insights, improved reasoning, and secure action workflows.
• Build components and services that integrate Agentic AI design patterns like AI Orchestration, Memory systems, RAG, Long horizon tasks, LLM-based models into the HackerOne platform, applying an AI-First approach to enhance vulnerability detection and security automation.
• Implement features for AI red teaming agents and evaluation tools that help identify risks in LLMs and applied AI systems, supporting safer model development.
• Collaborate cross-functionally with Product, Security Research, and Customer Success to translate customer needs into clear engineering requirements and deliverables.
• Develop and integrate APIs that enable secure interactions between AI models, internal services, and third-party systems, adjusting quickly as requirements evolve with Change Agility.
• Use metrics, evaluation data, and telemetry to validate model behavior and improve system performance in alignment with Data-Driven Decision Making.
• Break down complex AI and security problems into smaller, fundamental components, applying First Principles Problem Solving to deliver simple, scalable solutions.
• Stay current with emerging AI security trends, contributing findings and learnings to team discussions and implementation planning.

Minimum Qualifications

• 5+ years of experience as a software engineer
• Must be able and willing to come to the office once per week (typically Thursdays)
• Experience implementing features within production-grade AI or ML systems, including integrating LLMs or generative AI models into applications
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers
• Familiarity with model deployment workflows, evaluation techniques, or MLOps concepts
• Understanding of responsible AI development and basic AI safety considerations

Preferred Qualifications

• Experience contributing to AI development platforms, internal ML tooling, or experimentation workflows
• Exposure to agentic frameworks such as ReAct, AutoGen, LangChain, or Semantic Kernel
• Familiarity with prompt engineering, fine-tuning, RAG architectures, or LLM optimization techniques
• Experience working with cloud AI/ML services (AWS Bedrock, GCP Vertex AI, Azure ML)
• Familiarity with full-stack technologies such as Ruby on Rails, GraphQL, or React—especially for integrating AI capabilities into existing systems

Compensation Bands

Seattle, WA , Boston, Washington DC, or Austin, TX

$190K – $230K • Offers Equity Options

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