This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves working with cloud infrastructure and related technologies to enhance public safety solutions. - 5+ years experience in cloud infrastructure (AWS and/or Azure) - Strong hands-on experience with Kubernetes (EKS or AKS) - Experience deploying production-grade APIs (API Gateway/APIM) - Experience with managed AI services (Bedrock, Azure OpenAI, SageMaker, Azure ML) - Experience implementing CI/CD pipelines (GitHub Actions, Azure DevOps, etc.) - Strong understanding of IAM, RBAC, and cloud security best practices - Experience with containerization (Docker) and infrastructure-as-code (Terraform, Bicep, or CloudFormation) Qualifications - Preferred experience building or operating an internal developer platform - Experience with MLOps tooling (MLflow, model registry, evaluation pipelines) - ISO, SOC, NIST framework familiarity - Experience implementing RAG architectures and vector databases - Experience implementing AI governance, logging redaction, and content filtering - Multi-cloud architecture experience - Public sector or regulated environment experience (if applicable) Requirements - Versaterm does not use AI in the recruitment process - All stages of recruitment decisions are led by people, including our qualified acquisition team and our experienced hiring managers Company Description Versaterm is a global public safety solutions company helping agencies transform how they serve their communities. - Founded in 1977 - Building an ecosystem of intuitive tools designed for public safety agencies, forensic labs, court systems, schools, and other institutions - Focus on improving workflows to help customers achieve more efficient operations, better service, and more just outcomes - Commitment to equity, diversity, inclusion, and a barrier-free workplace

• Manage, scale, and optimize cloud environments used for data science workloads (primarily AWS, Databricks, dbt). • Provision, maintain, and optimize compute clusters for ML workloads (e.g., Kubernetes, ECS/EKS, Databricks, SageMaker). • Implement and maintain high-availability solutions for mission-critical analytics platforms. • Deep expertise in AWS resource management and provisioning, including IAM roles and permissions. • Develop CI/CD pipelines for model deployment, infrastructure-as-code (IaC), and automated testing using industry standard toolchains • Build monitoring, alerting, and logging systems for cloud and ML infrastructure (e.g., Datadog, CloudWatch, Prometheus, Grafana, ELK). • Automate provisioning, configuration, and deployments using tools such as Terraform and CloudFormation, GitHub actions, etc. • Enable and improve data ingestion, transformation, and model execution workflows through platform capabilities and automation. • Develop and maintain self-service capabilities for data scientists to provision and manage reliable, reproducible environments for research and development. • Collaborate with Data Engineering to maintain integrations between data pipelines and cloud systems. • Share responsibility for provisioning and operating application networking capabilities that support data platforms, including API gateways, CDNs, application load balancers, TLS, and WAFs. • Implement and operationalize data science security and compliance controls for data science platforms in alignment with enterprise cloud standards. • Conduct periodic risk assessments,best practice reviews, and remediation efforts to strengthen security and resiliency. • Support secure handling of sensitive financial data. • Partner with data scientists, machine learning engineers, and data engineers to deeply understand and support their needs and workflows within data-driven initiatives. • Serve as a technical advisor on cloud architecture, performance optimization, and production readiness for data and ML platforms. • Adopt and champion Agile, DevOps, and Platform Engineering practices (kanban, scrum, continuous improvement, automation, Everything-as-a-Service) • Demonstrate a strong, proactive focus on serving internal customers, prioritizing user experience, identifying opportunities to leverage automation and self-service to reduce toil and cognitive load for developers and researchers.

• Operate and support production-grade Kubernetes clusters, ensuring high availability, stability, scaling, networking, and security best practices. • Monitor system health, investigate incidents, perform root cause analysis, and support postmortem processes to drive continuous operational improvement. • Maintain and support CI/CD and release pipelines using GitHub Actions, Jenkins, and Azure DevOps. • Support Infrastructure as Code environments using Terraform, Terragrunt, and Helm, ensuring consistency and reliability across environments. • Assist in GitOps-based deployments with Argo CD, ensuring smooth and predictable releases. • Maintain observability and alerting systems using Prometheus, Grafana, and Loki/ELK, proactively identifying and resolving issues.

• As a Senior Cloud DevOps Engineer at MBI, you will take a hands-on role in designing, building, and maintaining our cloud infrastructure across Microsoft Azure and Amazon Web Services. • You will work in close partnership with the CTO, VP of Product, VP of Infrastructure, and CISO to ensure cloud platforms align with product delivery timelines, maintain operational excellence, and enforce security best practices. • Ensure fast, secure, and reliable software delivery through automation and DevOps best practices. • Manage multi-cloud environments on Azure and AWS, covering compute, storage, networking, and platform services. • Develop and maintain robust CI/CD pipelines to automate software build, test, and deployment processes. • Employ Infrastructure as Code (IaC) tools to automate provisioning and configuration of cloud resources. • Monitor and analyze system performance metrics, ensuring scalability, reliability, and cost optimization. • Work directly with the CISO and security team to ensure cloud environments meet security requirements and compliance standards.