Note: The job is a remote job and is open to candidates in USA. EdgeConneX is seeking a Manager, Cloud Services to lead and mentor DevOps, MLOps, and DataOps engineers while overseeing the engineering of its multi-cloud platform. The role combines team leadership and delivery oversight with hands-on work across cloud infrastructure, CI/CD, Kubernetes, AI/ML operations, data platforms, and enterprise technology.
Responsibilities
- Help oversee and mentor a small team of DevOps, MLOps, and DataOps engineers (consultants and 1-2 internal direct reports in the near-term), setting technical direction and day-to-day priorities under the Senior Director's guidance
- Translate the Senior Director's vision into execution by defining the procedures, standards, and practices that shape how the teams work
- Grow the team's capability through coaching, code review, hiring input, and career development
- Coordinate across the DevOps, MLOps, and DataOps functions to keep priorities, tooling, and standards aligned
- Own delivery for your teams' commitments: planning, tracking in Jira, and reporting progress to leadership
- Partner with enterprise technology, product engineering, security, and data teams as a trusted technical leader
- Evolve and enforce our infrastructure-as-code standard (set with the Senior Director): Terraform with Azure Verified Modules (pinned), one root and state per account/subscription, and PR-based workflows with automated review
- Lead CI/CD in GitHub Enterprise (GitHub Actions), including completing the migration from Azure DevOps
- Manage Kubernetes clusters (EKS and AKS) with GitOps-based delivery (ArgoCD or Flux) across Windows Server and Linux workloads
- Drive cloud governance automation across Azure, AWS, and GCP: custom RBAC, Azure Policy enforcement, secrets management (Key Vault), and Terraform state management
- Create and maintain Azure Enterprise Applications and App Registrations (SSO, API permissions, service principal lifecycle), and integrate Entra ID SSO/SCIM across platforms
- Build and operate the MLOps platform: model deployment and serving pipelines, model registry, and monitoring for AI/ML workloads, using MLOps tooling such as MLflow, Kubeflow, or Azure ML
- Design and build custom MCP (Model Context Protocol) servers and AI tooling to streamline how the organization uses AI, and enable rapid AI-assisted (“vibe coding”) development
- Support the DataOps platform and pipelines: ETL/ELT orchestration, data platform reliability, CI/CD for data (Synapse, Power BI reporting, data warehousing), and database schema migration and versioning (Liquibase, Atlas)
- Provide hands-on support to the enterprise technology team on infrastructure and identity needs
Skills
- 10+ years in cloud, DevOps, platform, or data/ML engineering, with at least 2 years leading or managing engineers (formal management or true player-coach)
- Expert, hands-on Terraform experience at scale: module design, state management, and multi-environment patterns
- Deep, hands-on expertise in both Azure and AWS (networking, RBAC, Key Vault, compute); familiarity with GCP
- Proven experience with cloud migrations and multi-cloud setups across Azure, AWS, and GCP
- Production experience with CI/CD systems and Git-based PR workflows
- Hands-on Kubernetes experience (EKS and AKS) and GitOps delivery with ArgoCD or Flux
- Working knowledge across at least two of the three disciplines (DevOps, MLOps, DataOps) and the ability to lead engineers in all three
- Experience with enterprise identity and SSO (Entra ID, SAML, SCIM, OIDC), including Azure Enterprise Applications and App Registrations
- Strong scripting and automation skills (PowerShell, Python, or Bash)
- Comfortable administering both Windows Server and Linux
- Solid written and verbal communication skills, with the ability to explain trade-offs to leadership and mentor engineers
- Demonstrated use of AI-assisted development and a track record of building automation and internal tooling
- An innovative mind with high technical aptitude; you spot opportunities to automate and improve, and you act on them
- Comfort operating in ambiguity in a newly formed, fast-growing team building foundational capabilities
- A collaborative mindset that defaults to partnership over gatekeeping across organizational boundaries
- Strong written and verbal communication; you explain trade-offs to leadership and mentor engineers with equal clarity
- Judgment about when to build versus buy, standardize versus accommodate, and move fast versus set guardrails first
- GitHub Actions strongly preferred
- Hands-on with MLOps tooling (MLflow, Kubeflow, SageMaker, or Azure ML) and DataOps database change management (Liquibase or Atlas)
- Experience building custom MCP servers or comparable AI integrations
- Experience leading an Azure DevOps-to-GitHub or comparable toolchain migration
- Familiarity with Jira/Atlassian and Coda, or comparable work-tracking and documentation tooling
- Background modernizing legacy applications (WebForms, .NET) toward containers and modern deployment patterns
- Azure SQL / SQL Managed Instance operational experience
- Relevant certifications (Azure, AWS, HashiCorp Terraform)
Benefits
- Remote work available within the U.S.; if remote, travel 1 week quarterly to the Herndon, VA HQ is expected.
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