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About
Everything we do is about making the future of human work more purposeful. We do this by leveraging state?of?the?art technologies, modern architecture, and industry experts to create AI?powered solutions that transform the way our clients do business. The new AI Transformation team will build on Crowes established AI foundation, furthering the capabilities of our Applied AI / Machine Learning team. By combining Generative AI, Machine Learning and Software Engineering, this team empowers Crowe clients to transform their business models through AI, irrespective of their current AI adoption stage. As a member of AI Transformation, you will help distinguish Crowe in the market and drive the firms technology and innovation strategy. The future is powered by AI, come build it with us. About The Team We invest in expertise. Youll have the time, space, and support to go deep in your projects and build lasting technical and strategic mastery. Youll 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.
About The Role
AI DevOps and Cloud Infrastructure Manager
leads teams responsible for designing, operating, and scaling AI/ML infrastructure, cloud platforms, and DevOps automation that support enterprise model training, inference, and generative AI workloads. This role is the strategy and execution of cloud?native, Kubernetes?based platforms that enable reliable, secure, and cost?efficient AI systems. As a manager, this position combines hands?on technical leadership with people management, delivery ownership, and strategic decision?making. The role oversees distributed compute environments, GPU clusters, CI/CD pipelines, and vector?search infrastructure while ensuring high availability, resilience, and compliance with security and responsible AI standards. The manager partners closely with AI engineering, data engineering, product, and security teams, serves as the primary technical owner for assigned initiatives, and communicates system risks, tradeoffs, and progress to leadership. Key responsibilities include: Leading engineering teams responsible for AI/ML infrastructure, cloud operations, and MLOps automation. Defining cloud, Kubernetes, and infrastructure strategy to support scalable model training, inference, and generative AI platforms. Guiding the design and operation of distributed compute environments, GPU clusters, and vector database infrastructure. Overseeing CI/CD pipelines that automate model training, testing, deployment, monitoring, and lifecycle management. Managing incident response, failure analysis, and reliability engineering across AI platforms. Directing performance testing, capacity planning, and cost optimization for AI infrastructure.
Ensuring compliance with cloud security, IAM practices, governance requirements, and responsible AI frameworks. Implementing multi?cloud resilience patterns, high availability, and automated failover for critical AI workloads. Supporting platform modernization initiatives, including adoption of optimized LLM runtimes and new orchestration technologies. Evaluating third?party infrastructure tools, GPU scheduling solutions, and platform enhancements. Communicating system status, dependencies, risks, and technical decisions to senior leadership. Managing 45 direct reports, including coaching, performance management, and career development. Owning project delivery, including budget, timelines, and quality of outcomes. Coordinating with sales and stakeholders on project sizing, feasibility, and strategic opportunities. Driving continuous improvement initiatives to advance DevOps maturity and AI infrastructure operational readiness.
Qualifications
7+ years of professional experience in DevOps, cloud engineering, MLOps, or platform engineering. 2+ years in engineering leadership or senior technical leadership roles. Expert proficiency with distributed cloud systems, Kubernetes, and infrastructure?as?code. Advanced ability to troubleshoot infrastructure, networking, container, and deployment issues. Proficiency in Python, Bash, or similar automation and scripting languages. Strong understanding of monitoring, observability, and reliability engineering patterns. Hands?on experience supporting infrastructure for ML or generative AI workloads. Strong leadership, communication, and cross?functional collaboration skills.
Preferred Qualifications
Bachelors degree in computer science, engineering, cloud computing, or a related field. Masters degree in a technical discipline. Cloud and AI certifications, including Azure (AZ900, AZ104, AZ305, AZ700, AZ800, AI?102) or equivalent AWS/GCP certifications. Extensive experience with Kubernetes platforms (EKS, AKS, GKE) and cloud ML services (Azure ML, SageMaker). Experience with GPU workload orchestration, optimization, and multi?tenant inference environments. Expertise in observability and distributed tracing (Prometheus, Grafana, CloudWatch, OpenTelemetry). Strong experience with Terraform and infrastructure governance at scale. Familiarity with service mesh architectures (Istio, Linkerd) and advanced deployment patterns (blue/green, canary). Advanced experience supporting generative AI platforms, including LLM inference runtimes (vLLM, TGI), RAG infrastructure, and vector databases (Pinecone, Weaviate, FAISS). Experience operating fine?tuned LLMs (LoRA, QLoRA), managing GenAI CI/CD pipelines, and implementing hallucination, drift, and reliability monitoring. Demonstrated ability to make strategic technical decisions within defined delivery and budget constraints.
We expect the candidate to uphold Crowes values of Care, Trust, Courage, and Stewardship. These values define who we are. We expect all of our people to act ethically and with integrity at all times. The application deadline for this role is 04/30/2026. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. Crowe is not sponsoring for work authorization at this time. The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Crowe, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $102,400.00 $204,100.00 per year. Crowe LLP provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, genetics, national origin, disability or protected veteran status, or any other characteristic protected by federal, state or local laws. Crowe will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, Los Angeles County Fair Chance Ordinance, San Francisco Fair Chance Ordinance, and the California Fair Chance Act. #J-18808-Ljbffr
Languages
- English
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