Build and operate an AI infrastructure platform: You will design, build, and operate cloud-native infrastructure and platform tooling that accelerates AI development across the company. This includes enabling teams to develop, deploy, and operate AI-powered services safely and efficiently in production environments.
Own the DevOps and infrastructure side of MLOps and Agentic Systems: You will focus on the operational foundations of AI systems, including CI/CD for AI workloads, scalable inference infrastructure, observability, cost management, and reliability. You will establish repeatable patterns and shared services that reduce friction for teams building AI-enabled applications.
Enable AI services, agents, and runtime platforms: You will build and maintain infrastructure to support AI services such as LLM-backed APIs, Model Context Protocol (MCP) servers, and agentic systems used by production applications. You will enable secure tool access, runtime orchestration, and isolation boundaries for AI-driven workloads.
Integrate MLOps capabilities into platform operations: You will apply MLOps concepts to improve platform operations, including using AI-driven approaches for monitoring, alerting, anomaly detection, and incident response across AI and non-AI systems. You will help evolve how the platform observes and operates complex AI-enabled systems at scale.
Establish governance, security, and operational guardrails: You will help define and implement infrastructure-level governance for AI systems, including access controls, deployment policies, auditability, and secure-by-default patterns. You will partner with security and compliance teams to ensure AI infrastructure aligns with organizational risk and regulatory requirements.
Provide technical leadership and enablement: You will act as a technical leader, influencing platform architecture and best practices across teams. You will mentor engineers and work closely with product, data, and application teams to align AI platform capabilities with business goals.

Requirements

A senior cloud and platform engineer: You have 8+ years of experience in cloud infrastructure, DevOps, or platform engineering roles, with deep expertise designing and operating distributed systems in production.
Experienced with MLOps and agentic platforms: You have direct exposure to ML/GenAIOps practices, such as monitoring, anomaly detection, predictive alerting, or automated remediation, applied to real production systems. 5+ years of MLOps experience is required.
Strong in cloud-native infrastructure: You are proficient in building and managing cloud environments, Kubernetes, containerized workloads and infrastructure-as-code tools such as Terraform.
Comfortable supporting AI workloads: You have hands-on experience supporting platforms that and host/run deep neural networks, including LLM runtimes (e.g., vLLM, llama.cpp), ML compiler stacks (e.g., LLVM/MLIR), and PyTorch-based production systems.
Security- and operations-minded: You have a strong understanding of infrastructure security, IAM, secrets management, and operational risk as it relates to AI-enabled systems.
A platform-focused technical leader: You operate effectively as a technical leader, influencing architecture and standards while remaining hands-on. You communicate clearly, collaborate well cross-functionally, and thrive in ambiguous problem spaces.
Forward-thinking and pragmatic: You are proactive and innovative, with the ability to introduce emerging agentic patterns while balancing operational maturity and long-term maintainability. You will help design and operate scalable benchmarking and evaluation frameworks for agentic AI systems, enabling quantitative measurement of accuracy, reliability, cost–performance tradeoffs, regression detection, and the impact of model, prompt, or architecture changes (including techniques such as LLM-as-a-judge), with tooling that is reusable and accessible across the organization.
Nice To Have: Experience with Pulumi, Experience with GCP, and Cloudflare, Experience with GHA and Harness, Experience with Go lang, Experiencing supporting Data Engineering Platforms, Exposure to Data Warehousing and ETL/ELT Tools or Operations.

Benefits

Unlimited PTO. Unplug and rejuvenate, however you want—whether that’s vacationing on the beach or at home on a mental-health day.
$1,000 Learning & Development Fund. No matter where you are in your career, always invest in your future. We encourage you to attend conferences, take classes, and lead workshops. We also host hackathons, brunch & learns, and other employee-led learning opportunities.
Remote-First Environment. People thrive in a flexible and supportive environment that best invigorates them. You can work from your home, cafe, or hotel. You decide.
Health Care and Financial Planning. We offer a comprehensive medical, dental, and vision insurance package for you and your family. We also offer a 401(k) for you to contribute.
Stay active your way! Get $138/month to put toward your favorite gym or fitness membership — wherever you like to work out. Prefer to exercise at home? You can also use up to $1,650 per year through our Fitness Fund to purchase workout equipment, gear, or other wellness essentials.
New Family Bonding. Primary caregivers can take 16 weeks off 100% paid leave, while secondary caregivers can take 4 weeks. Returning to work after bringing home a new child isn’t easy, which is why we’re flexible and empathetic to the needs of new parents.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

cloud infrastructureDevOpsplatform engineeringMLOpscloud-native infrastructureKubernetesinfrastructure-as-codedeep neural networksLLM runtimesPyTorch

Soft Skills

technical leadershipcommunicationcollaborationproblem-solvingproactiveinnovativeinfluencing architecturementoringcross-functional teamworkadaptability