AI DevOps and Cloud Infrastructure Engineer

divh2Your Journey at Crowe Starts Here / h2pAt Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, youre 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. Thats 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. / ppJob Description : / ppAbout Crowe AI Transformation / ppEverything 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. / ppThe 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. / ppAs 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. / ppAbout the Team / pulliWe 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. / liliWe believe in continuous growth. Our team is committed to professional development and knowledge-sharing. / liliWe 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. / li / ulpAbout the Role / ppThe 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. / ppAs 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. / ppKey responsibilities include : / pulliLeading engineering teams responsible for AI / ML infrastructure, cloud operations, and MLOps automation. / liliDefining cloud, Kubernetes, and infrastructure strategy to support scalable model training, inference, and generative AI platforms. / liliGuiding the design and operation of distributed compute environments, GPU clusters, and vector database infrastructure. / liliOverseeing CI / CD pipelines that automate model training, testing, deployment, monitoring, and lifecycle management. / liliManaging incident response, failure analysis, and reliability engineering across AI platforms. / liliDirecting performance testing, capacity planning, and cost optimization for AI infrastructure. / liliEnsuring compliance with cloud security, IAM practices, governance requirements, and responsible AI frameworks. / liliImplementing multi-cloud resilience patterns, high availability, and automated failover for critical AI workloads. / liliSupporting platform modernization initiatives, including adoption of optimized LLM runtimes and new orchestration technologies. / liliEvaluating third-party infrastructure tools, GPU scheduling solutions, and platform enhancements. / liliCommunicating system status, dependencies, risks, and technical decisions to senior leadership. / liliManaging 45 direct reports, including coaching, performance management, and career development. / liliOwning project delivery, including budget, timelines, and quality of outcomes. / liliCoordinating with sales and stakeholders on project sizing, feasibility, and strategic opportunities. / liliDriving continuous improvement initiatives to advance DevOps maturity and AI infrastructure operational readiness. / li / ulpQualifications / pulli7+ years of professional experience in DevOps, cloud engineering, MLOps, or platform engineering. / lili2+ years of experience in engineering leadership or senior technical leadership roles. / liliExpert proficiency with distributed cloud systems, Kubernetes, and infrastructure-as-code. / liliAdvanced ability to troubleshoot infrastructure, networking, container, and deployment issues. / liliProficiency in Python, Bash, or similar automation and scripting languages. / liliStrong understanding of monitoring, observability, and reliability engineering patterns. / liliHands-on experience supporting infrastructure for ML or generative AI workloads. / liliStrong leadership, communication, and cross-functional collaboration skills. / li / ulpPreferred Qualifications / pulliBachelors degree in computer science, engineering, cloud computing, or a related field. / liliMasters degree in technical discipline. / liliCloud and AI certifications, including Azure (AZ-900, AZ-104, AZ-305, AZ-700, AZ-800, AI-102) or equivalent AWS / GCP certifications. / liliExtensive experience with Kubernetes platforms (EKS, AKS, GKE) and cloud ML services (Azure ML, SageMaker). / liliExperience with GPU workload orchestration, optimization, and multi-tenant inference environments. / liliExpertise in observability and distributed tracing (Prometheus, Grafana, CloudWatch, OpenTelemetry). / liliStrong experience with Terraform and infrastructure governance at scale. / liliFamiliarity with service mesh architectures (Istio, Linkerd) and advanced deployment patterns (blue / green, canary). / liliAdvanced experience supporting generative AI platforms, including LLM inference runtimes (vLLM, TGI), RAG infrastructure, and vector databases (Pinecone, Weaviate, FAISS). / liliExperience operating fine-tuned LLMs (LoRA, QLoRA), managing GenAI CI / CD pipelines, and implementing hallucination, drift, and reliability monitoring. / liliDemonstrated ability to make strategic technical decisions within defined delivery and budget constraints. / li / ul / div