HackerOne
Software Engineer, Applied AI
Seattle (Remote)$166k–$203kfulltimemidAdded 1 month ago
About this role
HackerOne seeks an AI-focused Software Engineer to build next-generation AI security capabilities, including the Hai AI security agent. You'll develop LLM-powered features and integrations that enhance vulnerability discovery and security automation for thousands of customers.
What you'll do
- Build and integrate AI capabilities like LLM workflows, RAG pipelines, and orchestration components for vulnerability detection
- Develop features for Hai AI security agent enabling natural language insights and reasoning workflows
- Create APIs and services for secure interactions between AI models, internal systems, and third-party platforms
- Apply data-driven decision making to evaluate model performance and iterate on features based on measurable impact
- Partner cross-functionally with Product, Security Research, and Customer Success teams to translate user needs into solutions
- Stay current with emerging AI and cybersecurity trends and share learnings with the team
What they're looking for
- AI/Machine Learning engineering
- Large Language Models (LLMs)
- RAG (Retrieval-Augmented Generation)
- Python or similar backend languages
- API design and development
- Data-driven problem solving
- Security domain knowledge
- Agile adaptation to evolving frameworks
Benefits
- Remote work with flexibility (~50 miles from Seattle, Boston, Washington DC, or Austin)
- 1 day onsite per week (Thursdays) requirement
- Opportunity to work on cutting-edge AI security solutions
- Collaborative cross-functional team environment
- Inclusive company culture recognized as Most Loved Workplace for Young Professionals (2024)
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HackerOne
HackerOne builds AI-powered security solutions, including AI security agents that enhance vulnerability discovery and automation for enterprise customers. The company is hiring software engineers to develop LLM-powered features and integrate advanced AI capabilities into its security platform.
- Website
- hackerone.com
Likely interview questions
- Can you walk us through a project where you built or integrated LLM-powered features? How did you handle challenges around model reliability and latency?
- Describe your experience with RAG (Retrieval-Augmented Generation) pipelines or similar AI orchestration patterns. What metrics did you use to evaluate performance?