HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next.
Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills.
People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards.
About the role
For decades, every fast-moving company has been held back by smart people doing manual, repetitive work that should not require smart people. You will be part of a team whose job is to make every team at HackerRank - from Go-To-Market to Finance to Product - dramatically more effective, by building AI agents, automations, and platform capabilities that eliminate the work that should not be manual in the first place.
Most engineering roles put you deep inside one product surface. This one puts you across the whole company. In a given month you might be building a data analytics agent that answers ad-hoc product questions in Slack, writing an MCP connector that gives AI agents access to internal tooling, or designing the eval harness that lets the team ship agent changes without regressions.
What you will do
- Embed with internal teams - from Marketing to Product to Finance - to map workflows and identify the real bottlenecks which can be impacted by AI.
- Scope, prototype, and ship AI agents and automations that eliminate high-leverage manual work across the company.
- Own agents end-to-end after launch: monitor quality, triage failures, review outputs, and iterate based on real usage data.
- Design and build the shared AI Agents platform: orchestration, routing, reusable components, access controls, logging, rate limiting.
- Build evaluation harnesses that measure agent quality programmatically, catch regressions before they reach users, and give the team confidence to ship changes.
- Author and maintain MCP (Model Context Protocol) connectors that give AI agents access to HackerRank's internal tools, APIs, and data systems.
- Own the outputs you ship. Write and review code with the same rigor you would apply to any production system - secure, well-tested, and maintainable.
Who you are
- 1-4 years of software engineering experience with a track record of shipping production systems, not just demos or prototypes.
- Strong Python skills and solid fundamentals across the stack - you can build and deploy a service, wire it to APIs and databases, and keep it running.
- Hands-on experience building with LLMs (Anthropic, OpenAI, or similar) in production, including prompt engineering, context management, tool use, and debugging failure modes at real scale.
- You have built or operated structured evaluation pipelines for AI systems with metrics and regression detection.
- You diagnose before you build. You discover what is actually hampering productivity before jumping to a solution, and you are as likely to recommend a simple script or process change as a full agent.
- Comfortable with ambiguity and able to drive loosely defined problems to working solutions.
- Fluency with AI tools and agents - not just as a user, but as someone who builds production systems on top of them and understands their failure modes deeply enough to debug and improve them.
Even better if you have
- Experience with agentic frameworks (LangChain, CrewAI, Claude Agent SDK or similar).
- Hands-on experience authoring MCP servers or building tool connectors for AI agents.
- Experience with RAG pipelines grounded in structured data models - vector databases, hybrid search, re-ranking - and AI observability tooling (Langfuse, OpenTelemetry).
You will thrive in this role if
- You are as comfortable writing Python, reading an agent trace log, and sitting with a finance team to map their workflow. You ship things end-to-end and take pride in systems that are clean under the hood and actually get used.
- Ambiguity motivates you. You can work with non-technical stakeholders where direction evolves, and you turn loose ideas into working automations that get adopted.
- You use AI as a force multiplier, not a shortcut. You have built real fluency with LLMs and agents, and you actively look for ways to raise the quality and pace of your work through them - while understanding their failure modes well enough to catch regressions before users do.
Want to learn more about HackerRank? Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.
HackerRank is a proud equal employment opportunity and affirmative action employer. We provide equal opportunity to everyone for employment based on individual performance and qualification. We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
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