Software engineer jobs in Boston, MA

About the role

As a Senior Software Engineer on our AI Platform team, you will contribute directly to the development of our next-generation AI security capabilities, including our in-platform AI security agent, Hai . You will help develop AI-powered features that enhance vulnerability discovery, improve security analysis workflows, and expand how thousands of customers detect and respond to emerging threats. At HackerOne, we embrace a Flexible Work approach that gives us the freedom to do our best work while also fostering the connections and community that make us stronger. Reflecting this philosophy, this is a role targeted for candidates within ~50 miles of Seattle, WA , Boston, Washington DC, or Austin, TX . We believe this balance of proximity and flexibility gives Hackeronies the chance to occasionally come together – fostering collaboration, connection, and in-person moments that enrich our culture – while still preserving the benefits of remote work. Must be able and willing to come to the office once per week (typically Thursdays). 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 .

What you'll bring

• Must be able and willing to come to the office once per week (typically Thursdays).
• Must be able and willing to come to the office once per week (typically Thursdays)
• 5+ years of experience as a software engineer
• 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
• 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

Benefits

Locations