AI DevOps and Cloud Infrastructure Engineer

AI Dev Ops and Cloud Infrastructure Engineer

Your Journey at Crowe Starts Here: At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well‑being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80‑year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups.

That’s why we continuously invest in innovative ideas, such as AI‑enabled insights and technology‑powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry.

We are building on Crowe’s AI foundation, combining Generative AI, Machine Learning, and Software Engineering to empower clients across all AI adoption stages.

• We invest in expertise. You’ll have the time, space, and support to go deep in your projects and build lasting technical and strategic mastery. You’ll work with developers, product stakeholders, and project managers as a trusted leader and domain expert.
• We believe in continuous growth. Our team is committed to professional development and knowledge‑sharing.
• We protect balance. Our distributed team culture is grounded in trust and flexibility. We offer unlimited PTO, a flexible remote work policy, and a supportive environment that prioritizes sustainable, long‑term performance.

The AI Dev Ops and Cloud Infrastructure Engineer I (Senior Staff) designs, builds, and operates scalable, secure, and highly automated cloud environments that support the training, deployment, monitoring, and continuous delivery of AI and machine learning systems. This role serves as a subject‑matter expert in infrastructure automation, distributed compute orchestration, and cloud platform operations, ensuring AI workloads perform reliably across development, staging, and production environments.

• Architecting and maintaining cloud infrastructure for AI model training, inference services, and distributed compute workloads.
• Implementing infrastructure‑as‑code (IaC) to automate provisioning, configuration, scaling, and lifecycle management of cloud resources.
• Designing and operating CI/CD pipelines for automated model training, testing, and deployment of AI‑enabled applications.
• Optimizing Kubernetes clusters, GPU utilization, and compute scaling strategies to balance performance, reliability, and cost.
• Integrating AI models, inference endpoints, and data pipelines into cloud‑native platforms.
• Developing monitoring, logging, alerting, and observability solutions using modern telemetry and tracing tools.
• Troubleshooting issues across networking, containers, compute, storage, and model‑serving layers.
• Leading performance benchmarking, load testing, and reliability validation for AI systems.
• Documenting infrastructure architectures, operational runbooks, and engineering standards.
• Supporting automation for dataset ingestion, model versioning, artifact management, and ML testing.
• Ensuring compliance with cloud security, identity management, encryption, and responsible AI guidelines.
• Partnering with security teams to implement secure networking, IAM policies, and secrets management.
• Providing technical mentorship, design reviews, and cloud best‑practice guidance to junior engineers.
• Evaluating new cloud services, platform capabilities, and AI infrastructure tooling for adoption.

• 4+ years of experience in Dev Ops, cloud engineering, platform engineering, or infrastructure engineering.
• Strong proficiency with Kubernetes, Docker, and cloud orchestration platforms.
• Deep experience with CI/CD systems and deployment automation.
• Demonstrated ability to debug distributed systems and cloud networking issues.
• Proficiency in Python, Bash, or other automation/scripting languages.
• Strong communication skills and ability to collaborate across engineering and security teams.
• Willingness to travel occasionally for cross‑functional planning and collaboration.