• Manage and maintain cloud infrastructure on GCP (primary), with exposure to AWS • Perform day-to-day Kubernetes (GKS) operations, pod troubleshooting, node management, scaling, and resource tuning • Execute compliance infrastructure tasks: instance provisioning, security group updates, DNS changes, and certificate renewals • Support and maintain CI/CD pipelines built on ArgoCD and GitHub Actions • Assist engineering teams with onboarding applications to the CI/CD platform • Troubleshoot build failures, deployment issues, and rollback scenarios • Ensure deployment hygiene, proper tagging, versioning, and environment promotion • Monitor infrastructure health using Prometheus, Grafana, and AlertForge • Respond to alerts, triage production issues, and execute runbooks • Perform initial RCA (Root Cause Analysis) for production incidents and escalate when needed • Maintain and update runbooks and operational documentation • Write and maintain Terraform modules for infrastructure provisioning • Automate repetitive operational tasks using shell scripts, Python, or Go • Identify and implement improvements to reduce toil and manual effort • Contribute to internal tools and utilities that improve developer experience • Own infrastructure cost as a first-class metric drive continuous cost optimisation across compute, network, and storage

• Serve as the technical authority for your assigned product on every sales call • Validate technical feasibility, answer architectural questions, and remove blockers • Ensure clients feel technically confident moving forward with deals • Own a specific product line as its deep SME in the field • Manage the technical roadmap for your product within each sales opportunity • Collaborate with other FDEs when clients need multiple product integrations • Serve as the gatekeeper for product relevance within your assigned product line • Secure direct customer feedback before any feature launches • Validate solutions with live clients to ensure they solve actual business problems • Own technical accountability for your product line within each account • Work as part of the FDE Integration Team to ensure complete client integration • Remain engaged until your product is live, stable, and proving value • Translate client's unstructured problems into clean Pixalate configurations • Map specific data fields and business logic to our platform • Ensure clients are actually protected in their specific environment • Author a specific Use Case Document for every engagement • Define exactly how the client applies Pixalate to their business • Establish the official "Definition of Done" for each trial • Serve as the first line of defense against churn • Manually verify that data flowing into client dashboards matches the promised Use Case • Ensure clients experience their "Aha!" moment—seeing specific dollar savings or risk avoided—before contract signing • Facilitate detailed technical transfer to Customer Success after contract signing • Document custom configurations and Use Cases for ongoing support

• Establish highly available production and non-production environments with disaster recovery capabilities across Microsoft Azure regions. • Configure and manage virtual networks (VNets), subnets, firewalls, and routing. • Coordinate Site-to-Site (S2S) VPN connections with vendors (VeriPark, Fiserv) and validate CIDR/IP ranges. • Manage DNS configuration, SSL/TLS certificate exchange through Azure Key Vault, and Identity and Access Management (IAM) approvals. • Build and maintain Azure DevOps CI/CD pipelines, GitOps / Infrastructure-as-Code practices, and secure deployment/release coordination.

• Operate and optimize Kubernetes clusters, Istio service mesh, and Linux-based systems • Automate workflows using Go, Python, and Shell scripting • Build monitoring and observability solutions with Prometheus, Grafana, and Loki • Troubleshoot complex networking, storage, and system performance issues • Participate in on-call rotations and postmortem reviews to improve system resilience • Partner with AI/ML teams to ensure infrastructure readiness for model training and data pipelines