Senior Software Engineer

HackerOne is a global leader in Continuous Threat Exposure Management (CTEM). The HackerOne Platform unites agentic AI solutions with the ingenuity of the world’s largest community of security researchers to continuously discover, validate, prioritize, and remediate exposures across code, cloud, and AI systems. Through solutions like bug bounty, vulnerability disclosure, agentic pentesting, AI red teaming, and code security, HackerOne delivers measurable, continuous reduction of cyber risk for enterprises. Industry leaders, including Anthropic, Crypto.com, General Motors, Goldman Sachs, Lufthansa, Uber, UK Ministry of Defence, and the U.S. Department of Defense, trust HackerOne to safeguard their digital ecosystems. HackerOne was recognized in Gartner’s Emerging Tech Impact Radar: AI Cybersecurity Ecosystem report for its leadership in AI Security Testing and has been named a Most Loved Workplace for Young Professionals (2024). HackerOne is at a pivotal inflection point in the security industry. Offensive security is no longer optional – it is the standard for forward-thinking companies that want to build trust and resilience in a world where AI-driven innovation and adversaries are moving faster than ever. With the industry shifting, HackerOne stands apart: we combine the ingenuity of the largest security research community with a best-in-class AI-powered platform, trusted by the world’s top organizations. HackerOne Values HackerOne is dedicated to fostering a strong and inclusive culture. HackerOne is Customer Obsessed and prioritizes customer outcomes in our decisions and actions. We Default to Disclosure by operating with transparency and integrity, ensuring trust and accountability. Employees, researchers, customers, and partners Win Together by fostering empowerment, inclusion, respect, and accountability. Senior Software Engineer (IC4) Location: Pune Working model: On-site / in-office Position Summary As a Senior Software Engineer (IC4), you will lead the design and delivery of production AI systems that power HackerOne's next-generation security platform. You will architect agentic workflows, LLM-powered features, and evaluation frameworks that change how our customers detect, triage, and remediate vulnerabilities. You will ship production systems, set engineering standards for AI work across squads, and be measured on customer outcomes and system reliability. HackerOne is a global leader in offensive security solutions, combining AI with the ingenuity of the world's largest community of security researchers. As we continue to evolve into an AI-powered, human-in-the-loop security platform, we are investing in intelligent, scalable systems that help customers proactively identify and resolve vulnerabilities across their digital ecosystems. You will work closely with engineers, product managers, and designers across Pune, the Netherlands, and North America. This role blends senior technical execution with cross-functional leadership. You will drive meaningful outcomes, advance our AI engineering practices, and mentor engineers building applied AI capabilities. As we establish our Pune office, this role is designed for in-person collaboration. Working onsite will help build strong relationships, accelerate problem-solving, and foster a vibrant and connected engineering culture aligned with our global teams. Primary Responsibilities Success in this role will be accomplished by delivering on the responsibilities below in alignment with HackerOne's Talent Principles: - Lead production AI delivery by designing and shipping agentic workflows that integrate tool use, orchestration, retrieval, and human-in-the-loop patterns. Own these systems end-to-end, from architecture to rollout to post-launch operations. - Set the bar for AI engineering quality by defining and implementing evaluation frameworks, including golden sets, offline and online evals, experimentation pipelines, and prompt and version discipline. Embed these practices across squads. - Apply First Principles Problem Solving to break down ambiguous AI problems, define clear solutions, and deliver scalable, maintainable systems that combine AI with secure, reliable product experiences. - Adopt an AI-first approach by designing workflows that incorporate LLMs, tooling, retrieval, and human-in-the-loop patterns to improve product outcomes and engineering velocity across the team. - Practice Data-Driven Decision Making by defining success metrics, quality and latency trade-offs, and using data to guide experimentation and continuous improvement in AI systems. - Demonstrate Change Agility by adapting quickly to shifts in model capabilities, AI tooling, and priorities. Re-scope work effectively and keep cross-functional stakeholders aligned through change. - Lead execution of complex, cross-functional projects that bring AI capabilities into core product features, spanning backend, frontend, and platform layers. - Design, build, and maintain highly available, performant, and durable features across the platform, contributing to both AI product innovation and system reliability. - Collaborate across engineering, product, and design to align on priorities, clarify requirements, and deliver solutions that drive measurable customer impact. - Identify and address technical debt and system inefficiencies in AI and non-AI code paths, improving code quality, scalability, and developer experience within your team and across shared systems. - Mentor and grow engineers, especially on applied AI patterns, evaluation discipline, and production readiness for LLM-based systems. Contribute to a culture of learning and continuous improvement. Minimum Qualifications - 8+ years of professional software engineering experience in modern SaaS environments. - Hands-on experience building production AI-assisted features, LLM-powered workflows, or agentic systems at scale. You have taken at least one non-trivial LLM or agent system from prototype to production and operated it. - Strong working knowledge of agentic architectures, including tool use and function calling, workflow orchestration, retrieval and RAG, and human-in-the-loop patterns. - Strong working knowledge of LLM evaluation and experimentation, including golden sets, offline and online evals, regression detection, and prompt and version discipline. - Strong proficiency in at least one dynamically typed, object-oriented programming language such as Ruby, JavaScript, or Python, and experience building scalable backend systems. - Experience with relational databases (e.g., PostgreSQL) and cloud platforms (e.g., AWS) to design and operate distributed systems. - Proven experience delivering end-to-end technical projects, including defining scope, managing trade-offs, and driving execution in collaboration with cross-functional partners. - Able to explain how you evaluate and operate AI systems in production, covering quality metrics, evals, rollout strategy, observability, and failure modes. Preferred Qualifications - Experience with vector stores, embeddings, hybrid retrieval, and building observability for LLM and agent systems, such as tracing, cost and latency dashboards, and reasoning logs. - Experience implementing evaluation and experimentation frameworks at team or org scale, including feedback loops that close onto product and model improvements. - Experience improving engineering practices, workflows, or system design through reusable patterns or shared solutions, particularly for AI engineering. - Ruby on Rails - React JS - PostgreSQL - GraphQL - Amazon Web Services - Exposure to security domains such as vulnerability management, application security, or threat intelligence. Hiring Process - Recruiter Screen - Hiring Manager Interview - Take-home assignment - Technical interview #1 (coding) - Technical interview #2 (system design) Job Benefits: - Health (medical, vision, dental), life, and disability insurance* - Equity stock options - Retirement plans - Paid public holidays and unlimited PTO - Paid maternity and parental leave