Senior Software Engineer

AI Chopping Block; Pune District; On-site; INR 3,600,000 - 4,800,000; Full time

Benefits offered by this job

Health insurance

Equity stock options

Paid holidays and unlimited PTO

Paid maternity and parental leave

Job summary

AI Chopping Block is seeking a Senior Software Engineer based in Pune, India, to lead the design and delivery of production AI systems. The role involves architecting workflows and leading projects that integrate AI features into core products. Candidates should have 8+ years of experience in software engineering and expertise in AI-assisted systems.

The position offers competitive compensation, including health benefits and equity options. This is an on-site role in a dynamic work environment.

Qualifications

• 8+ years of professional software engineering experience in modern SaaS environments.
• Hands-on experience building production AI-assisted features.
• Strong working knowledge of agentic architectures and LLM evaluation.
• Proficiency in at least one programming language like Ruby, JavaScript, or Python.
• Experience with relational databases and cloud platforms.
• Ability to deliver end-to-end technical projects.

Responsibilities

• Design and ship agentic workflows for production AI delivery.
• Set AI engineering quality by implementing evaluation frameworks.
• Apply first-principles problem solving to AI challenges.
• Collaborate with various teams to align and deliver solutions.
• Mentor engineers on AI patterns and production readiness.

Skills

Software engineering experience

AI-assisted feature development

LLM-powered workflows

Agentic architectures

Proficiency in Ruby, JavaScript, or Python

Relational databases

Cloud platforms

Project delivery

Tools

PostgreSQL

AWS

React JS

GraphQL

Data observability tools

Job description

Senior Software Engineer

Location: Pune

Working model: On-site / in office

Shift: UK shift

First Level 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.

Primary Responsibilities

• 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.

Compensation band: 36‑48 LPA

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

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