Role Description The Reliability team owns the availability, performance, and operational excellence of Runpod’s global platform. While infrastructure teams build the systems, the Reliability team ensures those systems remain resilient, observable, and scalable under real-world production conditions. This team is responsible for: - Defining and enforcing reliability standards across engineering - Designing incident response processes and improving recovery times - Building observability systems and reliability tooling - Driving SLO adoption and production readiness reviews - Reducing operational toil through automation As a Site Reliability Engineer on the Reliability team, you will focus on ensuring the stability and resilience of Runpod’s distributed platform. You will partner with engineering teams to improve system design, strengthen observability, and prevent incidents before they happen. This role blends software engineering with production operations. You’ll work on reliability frameworks, SLO design, automation, and production hardening, reducing errors and improving performance across different services and infrastructure. This is a high-impact role central to maintaining trust with developers running critical AI workloads on Runpod. Your Impact - Increase platform uptime and reduce incident frequency and duration - Establish and operationalize SLIs/SLOs across services - Improve MTTR through better tooling, automation, and runbooks - Strengthen production readiness standards - Drive long-term systemic reliability improvements You will influence how reliability is defined and measured across Runpod and help build the operational backbone of the company. Responsibilities - Reliability Engineering - Define and implement SLIs/SLOs for critical services - Lead incident response and coordinate cross-team mitigation efforts - Conduct blameless postmortems and ensure corrective actions are completed - Perform production readiness reviews for new services and features - Identify systemic risks and drive preventative improvements - Observability & Monitoring - Design and improve monitoring, alerting, and dashboards (Prometheus, Grafana, etc.) - Improve signal-to-noise ratio in alerts and reduce alert fatigue - Build internal tooling for reliability tracking and reporting - Improve visibility into GPU performance and distributed systems health - Automation & Toil Reduction - Automate recurring operational workflows - Build tools and scripts (Python, Go, Bash) to eliminate manual processes - Improve deployment safety through automation and guardrails - Strengthen CI/CD reliability and release processes - Cross-Functional Reliability Advocacy - Partner with engineering teams to improve system resilience - Provide guidance on fault tolerance, scalability, and failure handling - Contribute to architectural discussions with a reliability-first mindset Qualifications - 5+ years of experience in SRE, Reliability Engineering, or Production Engineering - Strong Linux systems and Networking expertise - Experience managing containerized production systems - Strong understanding of distributed systems and failure modes - Experience defining and managing SLIs/SLOs - Proven incident response and postmortem leadership experience - Strong scripting or programming skills - Experience with monitoring and alerting systems - Excellent written communication skills - Successful completion of a background check Preferred - Experience with GPU infrastructure or AI/ML platforms - Experience improving reliability in high-growth or large scale environments - Familiarity with GPU observability tooling - Experience with Infrastructure as Code - Experience working in startup environments - Experience building internal reliability platforms or frameworks Benefits - The competitive base pay for this position ranges from $150,000- $200,000 USD. - Meaningful equity in a fast-growing company - everyone on the team receives stock options. - Generous medical, dental & vision plans. - Flexible PTO - take the time you need to recharge. - Most roles 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.

Role Description We are seeking a DevOps Engineer to join our Cloud Platform team and help build the infrastructure and tooling that powers our engineering organization. In this role, you will focus on automation, CI/CD, and cloud infrastructure, enabling teams to build, deploy, and operate services reliably and efficiently. You will play a key role in creating paved paths and self-service tooling that improve developer velocity while maintaining high standards for reliability, security, and performance. You will work closely with the Cloud Platform, SRE, and Data Engineering teams in a fast-paced environment where systems are built and tested in real-world conditions. Key Responsibilities - Automation & Platform Enablement - Build and maintain CI/CD pipelines that support the full software development lifecycle - Develop self-service tooling and standardized workflows for deployment and operations - Improve developer experience through automation, documentation, and engineering best practices - Help establish scalable platform capabilities that accelerate engineering teams - Cloud Infrastructure & Operations - Implement and manage cloud infrastructure using Infrastructure as Code - Deploy and support containerized workloads using Docker and Kubernetes - Maintain and improve development, staging, and production environments - Partner with Cloud Platform and SRE teams to ensure systems are scalable, reliable, secure, and cost-efficient - Reliability, Observability & Security - Implement observability solutions across logging, metrics, tracing, and alerting - Participate in incident response, root cause analysis, and continuous improvement efforts - Implement secure CI/CD pipelines, secrets management, and access controls - Contribute to operational readiness, reliability practices, and infrastructure resilience - Cross-Functional Collaboration - Partner with engineering teams to support deployment, infrastructure, and operational needs - Troubleshoot infrastructure, deployment, and runtime issues across environments - Contribute to platform standards, technical documentation, and engineering best practices - Help improve engineering workflows through automation and collaboration Qualifications - 3+ years of experience in DevOps, infrastructure, cloud platform, or related engineering roles - Strong experience with CI/CD systems and deployment automation - Hands-on experience with Docker and Kubernetes - Experience managing cloud infrastructure, preferably AWS - Familiarity with Infrastructure as Code tools such as Terraform or CloudFormation - Experience operating production systems with monitoring, logging, and alerting - Proficiency in scripting or programming languages such as Python, Bash, or Go - Solid understanding of Linux systems and networking fundamentals - Strong problem-solving skills and ability to work in a fast-paced environment - Strong written and verbal communication skills - U.S. citizenship and ability to obtain and maintain a U.S. Government security clearance if required Preferred Skills - Experience working on a cloud platform or internal developer platform - Familiarity with Site Reliability Engineering (SRE) practices, including SLIs, SLOs, and error budgets - Experience supporting data pipelines or analytics infrastructure - Knowledge of cloud security best practices - Experience optimizing cloud costs and infrastructure efficiency - Background supporting high-reliability, defense, or regulated environments - Experience working in small, fast-moving engineering teams or high-growth technology companies - Active or prior security clearance What Success Looks Like Within 12 months, success in this role looks like reliable, scalable CI/CD pipelines and deployment workflows that are broadly adopted across engineering teams. You will have improved developer velocity through automation and self-service tooling while strengthening observability, operational readiness, and incident response. You will also have helped reduce operational toil, improve infrastructure reliability, and build cloud platform capabilities that scale alongside HavocAI's engineering and product organizations. Benefits - 100% Employer paid Health, Dental and Vision Insurance for you and your families - Life Insurance (Employer Paid) - Ability to participate in the companies 401k program (Matching) - Unlimited PTO policy with an enforced 2 week minimum - Equity Package - Work / Home Office Stipend - Global Entry - 16 Week Paid Parental Leave - Monthly Health and Wellness Stipend

• Operate directly at the intersection of software engineering and infrastructure • Collaborate to resolve production challenges that span the entire stack—from the application code down to the network layer • Optimize the entire stack by tweaking database queries, tuning application thread pools, and adjusting kernel parameters • Review application source code in Java and Angular to identify memory leaks, race conditions, or inefficient logic • Identify single points of failure in our architecture and re-design them for redundancy and auto-recovery • Propose and implement code fixes directly to improve system-wide platform stability • Build internal tooling that empowers other software engineers to self-serve efficiently • Write automated scripts to ensure manual interventions are permanently engineered out of the ecosystem • Participate actively as a critical member of the on-call rota responding to major platform outrages

• Secure CI/CD pipelines at scale across the organization's CI/CD platforms with standardized security templates and automated policy enforcement, embedding static analysis (SAST), software composition analysis (SCA), container, infrastructure as code (IaC), and secrets scanning, with break build enforcement on critical and high severity findings • Administer the enterprise SAST and SCA platform (scan engine infrastructure, query tuning, severity calibration, finding triage) and maintain the exploitability knowledge base that distinguishes true positives from false positives to keep security fast and low friction • Build automated compliance tooling that detects required scans, validates pipeline configuration, and flags coverage gaps; audit pipeline posture across platforms and drive remediation directly with engineering teams • Support secure SDLC practices and security gates (SAST, SCA, container, IaC, DAST), threat modeling, SBOM generation, and dependency verification; coordinate with the DAST and penetration testing functions and act on bug bounty findings • Design and build the enterprise security operations platform and the automation that orchestrates DevSecOps workflows (scan state changes, triage, exemptions, intake, notifications), including AI-assisted vulnerability triage with appropriate guardrails, audit trails, and human oversight • Define and report security risk metrics, lead security audits and assessments, conduct supply chain and CVE incident response across the estate, and mentor junior team members • Lead security reviews of Generative AI applications, agentic workflows, and AI developer tools submitted through the enterprise AI intake process, assessing against OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic Applications, NIST AI RMF, MITRE ATLAS, and NBA Gen AI security policy and standards • Author and maintain NBA Generative AI security policy and standards, including controls for AI data protection, model and prompt security, agentic AI, MCP (Model Context Protocol) integration, and AI developer tooling • Evaluate and onboard Gen AI security tooling such as runtime guardrails, AI red teaming, browser and DLP controls, and MCP governance, and design and operate runtime AI security controls integrated into application pipelines and runtime • Govern enterprise security over AI developer tooling and the MCP server approval workflow, and partner with the Enterprise Gen AI, Cloud Infrastructure, GRC, Legal, and Privacy functions to align AI security controls with broader AI governance • Administer and operate the enterprise cloud security platform across a large multi-cloud estate (cloud posture, container, and IaC scanning); detect, prioritize, and drive remediation of misconfigurations and vulnerabilities against defined SLAs with infrastructure and application teams • Own cloud security scanning policy configuration and service account governance (scope, least privilege, credential rotation), lead platform lifecycle work, and perform technical security configuration assessments of cloud platforms • Own the Kubernetes security posture across a large cluster footprint, including admission control, RBAC, namespace isolation, network policies, and Pod Security Standards, and execute admission controller enforcement programs that move policies from audit to block in staged, owner-communicated rollouts with exception and rollback processes • Design and operate automated credential rotation across cloud identity and key management services (cross-account role assumption, grace periods, owner notifications) and lead the initiative to eliminate static access keys in favor of OAuth 2.0, OIDC, and role-based authentication • Manage the secrets lifecycle across cloud and pipeline secret stores with detection, alerting, and automated rotation, and build reporting that surfaces aging and non-compliant secrets