Senior Software Engineer, Platform

Primary Responsibilities

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 the evolution of the cloud-based execution platform for the AI security agent Hai, implementing features that enable natural language-driven security insights, improved reasoning, and secure action workflows.
• Design and implement core components for end-to-end execution of security agents, including agent execution frameworks, memory services, RAG services, and observability systems.
• Operate with an AI-first mindset, leveraging tools such as Claude Code and ChatGPT Enterprise to significantly improve productivity across coding, design documentation, on-call response, and customer escalation handling.
• 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 distributed systems and security problems into smaller, fundamental components, applying First Principles Problem Solving to deliver simple, scalable solutions.

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 working with cloud services like AWS, GCP or Azure.
• Experience implementing distributed system features within production-grade AI or ML systems, including integrating LLMs or generative AI models into applications
• Familiarity with model deployment workflows, evaluation techniques, or MLOps concepts
• Understanding of responsible AI development and basic AI safety considerations

Preferred Qualifications

• Experience working with cloud AI/ML services (AWS Bedrock, GCP Vertex AI, Azure ML)
• Experience with Agentic AI Ops, ML Ops.
• Exposure to agentic frameworks such as ReAct, AutoGen, LangChain, or Semantic Kernel
• Familiarity with full-stack technologies such as Ruby on Rails, GraphQL, or React—especially for integrating AI capabilities into existing systems

Compensation Bands

Seattle, Austin, Boston, DC$182K – $222K • Offers Equity

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