• Work closely with internal teams to become an expert on Skydio’s Deployment products, processes, specifications, and product roadmap • Deploy and ensure our cloud connected devices software and hardware are functioning and providing value as agreed in our customer’s ecosystem after it has been installed, configured, tested, and modified as per requirements. • Communicate with customers to ensure that all of their needs are understood and addressed • Collaborate with various internal departments to ensure that they fulfill all customer requests • Resolve complaints and keeping track of all processes that pertain to the client’s needs • Act as the customer’s representative to ensure that their demands are met with a focus on improving the customer experience • Track and manage all implementation projects with our large enterprise customers for successful delivery of technology and services. • Develop and maintain deployment and installation documentation, and documenting Standard Operating Procedures for the customer to ensure proper usage and value out of deployment. Quantify product feedback and briefing executives to drive software and hardware engineering to better fit our customers needs • Build customer loyalty through proactive support and account management • Build scalable processes for installation of cloud connected devices on Enterprise grade secure networks

• Design and implement cloud infrastructure primarily on AWS, including networking, security, runtime, data, and logging layers • Support and integrate with Azure and GCP environments where part of broader enterprise architectures • Build and maintain CI/CD pipelines for: • Application deployments (frontend and backend) • Serverless and container-based services • Infrastructure-as-Code promotion across environments using Terraform • Define environment strategy (dev / stage / prod), release workflows, and deployment safety mechanisms (rollback, blue/green) • Implement security and compliance guardrails (encryption, secrets management, IAM, audit logging, WAF/edge security) • Own observability and SLO readiness (monitoring, alerting, tracing, log aggregation, synthetic checks) • Support connectivity and operational patterns across enterprise systems, APIs, and third-party integrations • Partner with architects and engineers on capacity planning, performance optimization, cost control, and incident response

• Design, build, and maintain scalable and secure cloud infrastructure for AI and Big Data solutions, ensuring high availability and performance in a production environment. • Implement end-to-end automation for the complete Machine Learning (ML) lifecycle, including infrastructure for model training, real-time inference, and data processing. • Develop, manage, and optimise Infrastructure as Code (IaC) using tools like Terraform to provision and configure cloud resources consistently and efficiently. • Create, manage, and improve robust Continuous Integration and Continuous Delivery (CI/CD) pipelines to enable rapid and safe deployment of code, models, and infrastructure changes. • Manage and optimise Kubernetes clusters (e.g., AKS, EKS, or GKE) specifically tailored for running containerised data processing frameworks and GPU-enabled ML workloads at scale. • Establish advanced monitoring, logging, and alerting systems to ensure the health, performance, and cost efficiency of the data and AI platforms. • Implement security measures, access controls, and compliance frameworks to ensure data privacy, model governance, and adherence to security best practices across all environments. • Work closely with Data Scientists, AI Engineers, and Software Development teams to translate complex AI requirements into robust, deployable infrastructure solutions.

• Design and implement highly available, scalable, and secure cloud infrastructure architectures utilising Microsoft Azure services, including AKS, VNETs, Private Endpoints, Azure Firewall, Key Vault, and Azure Application Gateway. • Develop and maintain Infrastructure as Code using tools like Terraform or ARM Templates to provision and manage cloud resources in a repeatable and consistent manner. • Design, implement, and optimise robust CI/CD pipelines (e.g., using Azure DevOps, GitHub Actions, or GitLab CI) for both application deployment and infrastructure changes. • Administer, secure, and optimise Kubernetes clusters (preferably AKS), focusing on networking, scaling, security hardening, and performance tuning. • Implement comprehensive monitoring, logging, and alerting solutions using tools like Prometheus, Grafana, and Azure Monitor/Log Analytics to maintain platform health and identify issues proactively. • Enforce security best practices, implement policies (e.g., Azure Policies), and ensure all deployments comply with industry standards and internal IT security requirements. • Work closely with development, security, and product teams to define requirements, troubleshoot complex production issues, and mentor junior team members on DevOps methodologies and tools.