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, , 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

Location : Pune

Working model : On-site / in office

Shift : UK shift

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 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 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 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 evals, regression detection, and prompt and version discipline.
• Strong proficiency in at least 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 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.

Compensation band : 36-48 LPA

Hiring Process

We have multiple roles open and would like to have interviews in predefined schedule.

1. Recruiter Screen
2. Technical interview (coding) : dates July 6th to July 10th)
3. System Design + Managerial Interview : dates July 8th to July 16th

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
• Leaves of absence (including caregiver leave and leave under CO's Healthy Families and Workplaces Act)
• Employee Assistance Program

*

Eligibility may differ by country

We're committed to building a global team! For certain roles outside the United States, India, the U.K., and the Netherlands, we partner with as our Employer of Record (EOR).

Visa/work permit sponsorship is not available.

Employment at HackerOne is contingent on a background check.

HackerOne is an Equal Opportunity Employer in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, pregnancy, disability or veteran status, or any other protected characteristic as outlined by international, federal, state, or local laws.

This policy applies to all HackerOne employment practices, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. HackerOne makes hiring decisions based solely on qualifications, merit, and business needs at the time

• For US based roles: Pursuant to the San Francisco Fair Chance Ordinance, all qualified applicants with arrest and conviction records will be considered for the position.

• 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 non-trivial LLM or agent system from prototype to producti
• 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 evals, regression detection, and prompt and version discipline.
• Strong proficiency in at least 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.
• 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 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.