Runpod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022, we are a rapidly growing, well-funded company with a remote-first organization spread globally. Our mission is to empower innovators and enterprises to unlock AI's true potential, driving technology and transforming industries. Join us as we shape the future of AI.
We believe AI agents will change how every team at RunPod works. We’re building them internally and expanding them externally to our customers. You’ll join a small, experienced team that has already shipped agents people use every day, and you’ll help make them more capable, more reliable, and more widely adopted across the company. The work spans agents that help people work with data and the shared tooling that lets more of RunPod build with AI. As these agents mature, we plan to bring what works to our customers, and you’ll have the chance to help shape and build those customer-facing experiences. This is a hands-on engineering role for someone who likes taking agents from promising to indispensable, and who cares as much about trust and accuracy as about capability.
Responsibilities:
Build, extend, and improve internal AI agents that help people across the business get work done faster, regardless of their technical background.
Help take proven internal agents to customers, adapting them for external use with the reliability, security, and polish that customer-facing products require.
Improve the accuracy, reliability, and explainability of agent outputs, so people can trust what they get back.
Contribute to the shared tooling and infrastructure that make it easier and safer to build and run agents, both inside the company and for customers.
Define and expand how we measure agent quality, including accuracy, latency, cost, and adoption, and build the evaluation practices that keep us honest.
Harden agent systems for production, with strong attention to security, access controls, and observability.
Work closely with your teammates and stakeholders across the company, including product, to find high-value use cases, gather feedback, and drive adoption.
Keep up with the fast-moving agent ecosystem and help the team decide what’s worth adopting, what’s worth building, and what’s worth contributing back.
Requirements:
Hands-on experience building and shipping LLM-powered agents or applications in production, beyond prototypes.
Strong software engineering skills in Python, and comfort working in and improving an existing codebase alongside other engineers.
Solid SQL skills and familiarity with modern data tooling.
Experience with core agent techniques, such as tool calling, retrieval, context management, and multi-step planning.
Rigor in evaluating LLM systems, including building eval sets, catching regressions, and making trade-offs between quality, latency, and cost.
A collaborative working style: you give and take code review well, share context generously, and can work with non-technical users to understand what they need.
The ability to explain your results clearly in writing and turn them into decisions.
Preferred:
Experience shipping customer-facing AI products or features, including the guardrails, scale, and reliability work they need.
Experience building internal tools or platforms used by multiple teams.
Experience with agent frameworks, tool and connector protocols, or LLM observability tooling.
Data engineering experience.
Contributions to open-source AI or data projects.
What You’ll Receive:
The competitive base pay for this position ranges from ($100,000 - $130,000). This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location
Meaningful equity in a fast-growing AI infra company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside.
Generous medical, dental & vision plans
Flexible PTO- take the time you need to recharge
Most roles have are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication
Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale.
$1,200 Home Office & Equipment Stipend- We set you up for success from day one with gear and support to create your ideal workspace
Runpod is committed to maintaining a workplace free from discrimination and upholding the principles of equality and respect for all individuals. We believe that diversity in all its forms enhances our team. As an equal opportunity employer, Runpod is committed to creating an inclusive workforce at every level. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or any other characteristic protected by law. We welcome every qualified candidate eligible to work in the United States; however, we are currently unable to sponsor employment visas.
Skills Required
- Hands-on experience building and shipping LLM-powered agents or applications in production
- Strong software engineering skills in Python and experience working in an existing codebase
- Solid SQL skills and familiarity with modern data tooling
- Experience with tool calling, retrieval, context management, and multi-step planning
- Experience evaluating LLM systems, including building evaluation sets and catching regressions
- Ability to balance quality, latency, and cost in LLM systems
- Collaborative working style and ability to work with non-technical users
- Ability to explain results clearly in writing and turn them into decisions
- Experience shipping customer-facing AI products or features
- Experience building internal tools or platforms used by multiple teams
- Experience with agent frameworks, tool and connector protocols, or LLM observability tooling
- Data engineering experience
- Contributions to open-source AI or data projects
Runpod Compensation & Benefits Highlights
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Healthcare Strength — Company materials and third‑party listings indicate fully paid health benefits for full‑time employees, with dental and vision coverage also highlighted. Health coverage is described as strong for employees, with the employer covering a substantial share of the employee premium.
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Equity Value & Accessibility — Meaningful equity or stock options are consistently positioned as a core part of compensation. This setup allows employees to participate in the company’s growth alongside salary and other benefits.
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Leave & Time Off Breadth — Flexible or unlimited PTO, along with paid sick time and holidays, is frequently emphasized. These policies are presented as generous for a fast‑growing, remote‑first startup.
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What We Do
Runpod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022, we are a rapidly growing, well-funded company with a remote-first organization spread globally. Our mission is to empower innovators and enterprises to unlock AI's true potential, driving technology and transforming industries. Join us as we shape the future of AI. We are building Cloud services focused on accelerating AI adoption. Whether you're an experienced ML developer training a large language model, or an enthusiast tinkering with stable diffusion, we strive to make GPU compute as seamless and affordable as possible.
Why Work With Us
Our Guiding Virtues Give a sh*t - We want to work with people who care - about our customers and about each other. Look in the mirror - We deeply reflect on our own actions and seek to better ourselves. Courage over comfort - We tackle hard truths and tough situations directly, even when it makes us uncomfortable.
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Employees work remotely.
We’re remote-first, offering flexibility with virtual tools for collaboration. For those nearby, we have coworking spaces in SF and Seattle. Enjoy the choice of office or remote work, with a focus on flexibility and work-life balance.






