Engineer, Development Operations - Archimedes

Responsibilities

• Collaborate closely with application development teams to optimize build, test, release, and deployment workflows, reducing cycle time and increasing release frequency.
• Architect, implement, and optimize multi-stage CI/CD pipelines using Azure DevOps, YAML, environments, templates, deployment groups, release gates, and GitHub Actions.
• Serve as a technical owner for Infrastructure-as-Code practices, ensuring cloud infrastructure, networking, security controls, and platform services are provisioned, managed, and governed through Terraform and version-controlled automation.
• Develop reusable Terraform modules, Bicep templates, ARM templates, shared pipeline templates, and platform blueprints to standardize deployment patterns across environments.
• Automate infrastructure provisioning using Terraform, Bicep, ARM templates, Azure CLI, and PowerShell, enforcing modular reusable patterns, policy-as-code, and enterprise guardrails.
• Implement policy-as-code, compliance-as-code, and governance automation using Azure Policy, Management Groups, RBAC, Defender for Cloud, and related Azure governance capabilities.
• Manage and optimize package repositories including Azure Artifacts, GitHub Packages, NuGet, and npm, ensuring artifact integrity, traceability, and lifecycle control.
• Support IT governance of the code release lifecycle, including semantic versioning, automated tagging, changelog generation, approval workflows, and deployment auditability.
• Evaluate, integrate, and manage the DevOps toolchain, including build servers, artifact repositories, dependency scanners, secrets managers, testing tools, and security scanning tools.
• Design and deliver secure, scalable cloud-native architectures using Azure App Services, AKS, Azure SQL, Azure Functions, API Management, Key Vault, Storage Accounts, and related Azure services.
• Design, implement, and support enterprise integration patterns utilizing REST APIs, GraphQL APIs, SOAP services, webhooks, message queues, event-driven architecture, and managed integration services.
• Partner with software engineering teams to establish API lifecycle management, API security controls, automated testing, monitoring, and deployment patterns.
• Partner with software and data analytics teams to support deployment of data pipelines, Azure Data Factory, Databricks, Synapse, Data Lake, Event Grid, Event Hub, and related data platform integrations.
• Build and maintain automated deployment pipelines for Databricks workspaces, notebooks, jobs, clusters, Unity Catalog, libraries, data products, and supporting cloud infrastructure.
• Enable infrastructure and DevOps support for machine learning, ETL, analytics, data lake, and lakehouse environments, ensuring secure service access, RBAC, observability, and cost controls.
• Support MLOps platform capabilities, including model training, validation, deployment, monitoring, model registry integration, and governance automation.
• Partner with data scientists and data engineers to operationalize machine learning, AI, and advanced analytics workloads using Azure Machine Learning, Databricks ML, MLflow, and CI/CD automation.
• Support enterprise automation initiatives utilizing robotic process automation, workflow orchestration, AI-powered automation, and low-code/no-code automation platforms.
• Use pipeline analytics and deployment telemetry to identify bottlenecks, reduce build/test times, improve developer feedback loops, and increase delivery reliability.
• Implement shift-left testing strategies, including unit, integration, regression, infrastructure, and performance testing automation directly within CI/CD pipelines.
• Apply DevSecOps practices within the CI/CD lifecycle, including SAST, DAST, secrets scanning, dependency scanning, code signing, artifact provenance validation, and container security.
• Integrate security tools such as Snyk, CredScan, OWASP ZAP, Aqua Security, Defender for Cloud, or similar platforms into the software delivery lifecycle.
• Integrate infrastructure validation into the delivery process using tools such as Pester, InSpec, Terratest, or similar testing frameworks.
• Lead containerization and deployment strategies using Docker, Helm, Azure Container Registry, and AKS, supporting secure cluster design, ingress, network isolation, pod security, and autoscaling.
• Implement blue-green, canary, and ring deployments for applications and APIs using traffic routing, feature flags, deployment slots, and progressive release practices.
• Build self-service platforms and reusable DevOps tooling to streamline developer onboarding, environment provisioning, service connection governance, and deployment configuration.
• Maintain golden pipeline templates, DevOps starter kits, Terraform modules, automation scripts, and reusable deployment patterns to standardize delivery across teams.
• Conduct failure mode analysis, root cause analysis, and resilience engineering using Azure Chaos Studio, Availability Zones, health probes, auto-healing logic, and operational telemetry.
• Maintain architectural runbooks, deployment documentation, operational SOPs, environment diagrams, and audit evidence supporting change management and compliance requirements.
• Serve as a Tier 2/3 escalation point for platform, deployment, automation, pipeline, integration, and cloud infrastructure issues.
• Operate within an ITSM framework, contributing to incident, change, release, and problem management practices.
• Participate in, adhere to, and support compliance, people and culture, and learning programs.

Qualifications

• Education: Bachelor’s degree or equivalent work experience required.
• Certification/Licenses: Certifications such as Microsoft Certified DevOps Engineer Expert, Azure Solutions Architect Expert, or Azure Security Engineer Associate preferred.
• Experience: 6+ years in DevOps, Cloud Engineering, or SRE roles with a focus on Azure required.
• Advanced experience with Azure DevOps, ARM/Bicep, and Terraform for pipeline and infrastructure automation required.
• Proficient in scripting with PowerShell, Bash, or Python for automation and tooling integration.
• Strong knowledge of Azure-native services, including App Services, AKS, Key Vault, Load Balancers, VNETs, Application Gateway, and Azure DNS required.
• Experience supporting CI/CD, automation, and deployment patterns for Azure Databricks, Azure Data Lake Storage Gen2, Delta Lake, Unity Catalog, and lakehouse environments preferred.
• Familiarity with DataOps, MLOps, machine learning deployment automation, AI platform operations, and analytics engineering workflows preferred.
• Exposure to Azure Machine Learning, Azure OpenAI, Databricks ML, MLflow, model registries, and automated model deployment patterns preferred.
• Hands-on experience with containerization and orchestration in AKS, including networking, ingress controllers, and horizontal pod autoscaling required.
• Familiarity with Azure Active Directory, RBAC, and service principals for secure identity and access management preferred.