• Design, deploy, and operate Azure landing zones and shared services for large enterprise environments. • Build and manage core compute and platform services, including: Azure Virtual Machines, VM Scale Sets, Azure Kubernetes Service (AKS) and container registries (ACR), and Platform services such as App Services, Functions, and Azure Automation. • Implement resilient, scalable solutions using availability zones, ASGs, load balancers, and backup/recovery patterns. • Apply governance, RBAC, Azure Policy, Blueprints/management groups across subscriptions and tenants. • Experience assessing the customer environment using tools like Azure Migrate and performing Migration Planning and Assessments. • Experience with Creating wave plans, building server inventory for large/Medium scale migrations. • Implement and maintain Infrastructure as Code (IaC) using tools such as Terraform and/or Bicep, and configuration management (e.g., Ansible). • Build CI/CD pipelines for infrastructure and application workloads using Azure DevOps, GitHub Actions, or similar Git-based toolchains. • Standardize and templatize platform components (modules, pipelines, patterns) to support internal developer platforms and self-service provisioning. • Integrate security and policy-as-code into pipelines (linting, approvals, guardrails) to ensure compliant deployments. • Collaborate with SRE/operations teams to automate day-2 operations (patching, scaling, scheduled maintenance, routine changes). • Experience to Operate the kubernetes cluster on Azure using tools like CNI, Ingress Controllers, Service Mesh, Network Policies. • Experience to build automation using Ansible playbooks, Python, PowerShell. • Experience to build and deploy application and infrastructure using CICD tools like Azure DevOps/GitLabCI/Harness/Jenkins. • Design and implement Azure networking architectures, including: Hub-spoke topologies, VNets, subnets, and VNet peering, VPN Gateways, ExpressRoute, and hybrid connectivity. • Troubleshoot complex networking issues across hybrid and multi-cloud footprints. • Configure and tune Azure Monitor, Log Analytics, Application Insights, and related tooling for logging, metrics, and alerting. • Contribute to SRE-style practices such as runbooks, incident response patterns, and reliability-focused automation.

• Lead the end-to-end technical execution of frontend initiatives within the platform engineering team, from shaping requirements and writing technical design proposals through implementation, testing, and production release. • Translate department initiatives and team goals into scalable frontend architecture decisions, balancing speed, quality, and long-term maintainability. • Contribute meaningfully to the evolution of our internal developer portal and other UI applications, improving shared libraries, platform capabilities, and system design. • Operate effectively in ambiguous problem spaces identifying risks, validating assumptions, and proactively de-risking solutions before they impact delivery. • Ensure the long-term health of the codebase by reducing technical debt, improving test coverage, and setting high standards for code quality and performance. • Collaborate closely with the team to align on trade-offs, API contracts, and non-functional requirements such as performance, reliability, and security. • Proactively monitor, debug, and resolve production issues, contributing to observability, incident response, and post-mortems that strengthen our systems over time. • Mentor and support other engineers through thoughtful code reviews, technical guidance, and knowledge sharing that raises the bar for the entire team. • Maintain an active awareness of business priorities and customer impact, ensuring your technical decisions align with Weave’s broader product and company goals.

• Design, deploy, and operate workloads on Azure Kubernetes Service (AKS) to meet security, resilience, and performance goals • Lead AKS bootstrapping, cluster/node/pod configuration, and operational support activities • Build automated deployment templates for customers to provision AKS instances • Implement and maintain CI/CD and GitHub build/release pipelines for Dev, Stage, and Production environments • Configure autoscaling (Horizontal Pod Autoscaler, Cluster Autoscaler) and integrate Azure Container Instance (ACI) where appropriate • Implement Pod security policies, node-to-node encryption, and enforce NIST-aligned security controls when deploying container images • Integrate AKS logs (application, event, cluster, user activity, diagnostics) into Azure Event Hub or Storage and enable real-time monitoring • Manage authentication and authorization for cluster access using managed identities, service principals, certificates, and secrets • Deploy and manage HTTPS Ingress controllers and TLS certificate management for Kubernetes services • Use governance and scanning tools to monitor images, runtime, vulnerabilities, registries, and hosts

Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career. Job Title Senior AI Platform Engineer Location Remote Time Zone Flexible / Aligned to HQ Time Zone Role Overview This role sits at the intersection of AI engineering and platform development. As a Senior AI Platform Engineer, you will own the contextual intelligence layer that powers our AI agents — ensuring they understand, reason, and act with precision across our SaaS ecosystem. You will work at the cutting edge of how structured knowledge is used to make AI agents smarter and more reliable. This is a role for an engineer who thinks deeply about context, meaning, and how machines can be equipped to make better decisions — and who can also build the frontend surfaces that make those capabilities accessible to end users. Key Responsibilities - Design and maintain semantic context layers — knowledge graphs, ontologies, and structured context stores — that inform agent behaviour - Develop full stack features that allow users to configure, monitor, and control AI agents through intuitive interfaces - Integrate RPA agents with semantic reasoning capabilities, enabling context-aware automation at scale - Build and maintain data platform frontends that provide real-time visibility into agent activity and data flows - Work closely with product and data science teams to translate business requirements into intelligent automation solutions - Champion engineering quality through testing, documentation, and architectural consistency Required Qualifications - Senior-level full stack engineering experience - Deep understanding of semantic technologies — knowledge graphs, RDF/OWL, ontologies, or entity resolution - Hands-on experience building or consuming AI agent frameworks - Strong frontend skills with React or similar, including data visualisation libraries such as D3.js or Recharts - Experience with Python-based backends and ML service integration - Comfort working in fast-moving SaaS product environments - Must have prior remote work experience and demonstrated ability to collaborate asynchronously across distributed teams Preferred Qualifications - Experience with graph databases such as Neo4j or Amazon Neptune - Exposure to NLP pipelines and named entity recognition (NER) - Contributions to open-source AI or semantic tooling - Experience with enterprise-scale knowledge management systems Tools & Technology - Python / Node.js - React / TypeScript - Graph or semantic databases (Neo4j, Amazon Neptune, or similar) - LLM APIs and agent orchestration frameworks - Data visualisation tooling (D3.js, Recharts, or similar) - Slack, Zoom, Google Workspace Please Note It is crucial that you complete the application form in full. As part of the application process, you will be required to complete a short technical assessment. If your application is successful, you will receive an email confirming next steps. Applications that are not completed in full will not be considered for any open roles. We connect top talent with vetted employers, competitive pay, and real growth opportunities.