Runpod Logo

Runpod

Software Engineer, Agents

Posted 13 Minutes Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
100K-130K Annually
Entry level
Remote
Hiring Remotely in USA
100K-130K Annually
Entry level
Build and improve production LLM-powered agents for internal teams and customers. Develop shared agent tooling and infrastructure, improve accuracy, reliability, explainability, security, and observability, and establish evaluation practices covering quality, latency, cost, and adoption. Collaborate with product and business stakeholders to identify use cases, drive adoption, and evaluate emerging agent technologies.
The summary above was generated by AI

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.

Similar Jobs at Runpod

2 Hours Ago
Remote
USA
140K-180K Annually
Mid level
140K-180K Annually
Mid level
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Own the financial planning and analytics for Runpod’s GPU infrastructure and capacity. Responsibilities include capacity and utilization reporting, tranche fill analysis, capex and cash forecasting, GPU ownership modeling, fleet unit economics, pricing floors, infrastructure investment evaluation, commercial negotiation support, scenario analysis, and variance reporting. The role builds finance processes and dashboards from scratch while partnering with Infrastructure, Data Center Operations, and Sales.
Top Skills: Asc 842Business Intelligence ToolsGoogle SheetsExcelSQLUs Gaap
2 Hours Ago
Remote
USA
140K-180K Annually
Mid level
140K-180K Annually
Mid level
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Own finance analytics for Sales and GTM, including pipeline forecasting, revenue projections, pricing and deal modeling, sales commission administration, and marketing ROI analysis. Partner with Sales, Marketing, and leadership to align targets, improve reporting infrastructure, and guide budget allocation. This hands-on role builds scalable processes from the ground up and translates financial data into actionable business recommendations.
Top Skills: Bi ToolsCrm SystemsExcelGoogle SheetsSlack
4 Days Ago
Remote
USA
125K-220K Annually
Senior level
125K-220K Annually
Senior level
Artificial Intelligence • Cloud • Software • Infrastructure as a Service (IaaS)
Lead Runpod’s security organization and own the security posture of its cloud platform, infrastructure, and corporate environments. Responsibilities include security strategy, cloud and application security, SecOps, GRC, compliance certifications, secure software development, threat modeling, vulnerability management, incident response, vendor risk, security automation, and infrastructure security. Build and mentor a distributed security team while partnering with Engineering, Infrastructure, Product, GTM, and Legal to protect customer AI workloads and support scalable growth.
Top Skills: Ci/CdCloud InfrastructureGpu ClustersHipaaIamIso 27001KubernetesLinuxNetworkingSoc 2VirtualizationZero-Trust Architecture

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account