Managing Director-Delivery

Anblicks; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Anblicks seeks a Director/Senior Manager to govern the enterprise cloud platform and AI enablement in a multi-cloud world. You will lead strategy, architecture, and operations to enable secure, scalable, and cost-efficient cloud services and AI capabilities.

You will drive platform engineering, automation, and SRE practices while partnering with security, data, and product teams to deliver enterprise-scale solutions.

Qualifications

• 12+ years in Cloud/Platform Engineering, DevOps, SRE, or related field.
• 5+ years leading cloud/platform engineering teams.
• Strong experience with AWS, Azure, GCP, or multi-cloud environments.
• Hands-on Kubernetes, IaC, CI/CD, cloud networking, observability, and security.
• Experience building and operating enterprise-scale cloud platforms.
• Experience enabling AI/ML or Generative AI platforms within cloud environments.

Responsibilities

• Lead the strategy, engineering, and operations of the enterprise cloud platform.
• Build and support AI platform capabilities including GenAI, LLM, and AI services.
• Define and execute cloud platform strategy and roadmap.
• Lead modernization and adoption of cloud-native technologies.
• Drive IaC and automation initiatives to improve developer experience.
• Oversee cloud & Kubernetes operations, SRE practices, and governance.
• Communicate platform strategy and investments to senior leadership.

Skills

Leadership experience

Strategic planning

Cross-functional collaboration

Cloud architecture

SRE/DevOps mindset

Security governance

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Kubernetes

Terraform

CloudFormation

Pulumi

CI/CD pipelines

Cloud networking

Observability

Security

Job description

Director / Senior Manager - Cloud Platform Engineering & AI Enablement

Role Summary

Lead the strategy, engineering, and operations of the enterprise cloud platform. Responsible for enabling secure, scalable, and cost-effective cloud infrastructure, platform services, automation, developer productivity, and AI platform capabilities.

Key Responsibilities

AI Platform Enablement

• Build and support enterprise AI platform capabilities including GenAI, LLM, and AI development services.
• Enable secure access to platforms such as Azure AI, Azure OpenAI, AWS Bedrock, Vertex AI, and similar services.
• Establish governance, security, and cost controls for AI workloads.
• Accelerate adoption of AI-assisted engineering and business solutions.

Cloud Platform Leadership

• Define and execute the cloud platform strategy and roadmap.
• Establish cloud architecture standards, governance, and engineering best practices.
• Lead modernization and adoption of cloud-native technologies.

Platform Engineering & Automation

• Build self-service platform capabilities for application teams.
• Drive Infrastructure as Code (Terraform, CloudFormation, Pulumi) and automation initiatives.
• Improve developer experience through platform engineering and CI/CD capabilities.

Cloud & Kubernetes Operations

• Lead enterprise container and Kubernetes platform initiatives.
• Ensure platform reliability, scalability, observability, and disaster recovery readiness.
• Implement SRE practices and operational excellence frameworks.

Security, Governance & FinOps

• Implement cloud security, compliance, and governance controls.
• Drive cloud and AI cost optimization through FinOps practices.
• Establish operational metrics, SLOs, and platform performance KPIs.

Leadership & Stakeholder Management

• Lead teams of cloud engineers, platform engineers, DevOps, and SRE professionals.
• Partner with application, security, data, and product teams.
• Communicate platform strategy and investment priorities to senior leadership.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 12+ years in Cloud Engineering, Platform Engineering, DevOps, SRE, or Infrastructure Engineering.
• 5+ years leading cloud/platform engineering teams.
• Strong experience with AWS, Azure, GCP, or multi-cloud environments.
• Hands-on expertise in Kubernetes, Infrastructure as Code, CI/CD, cloud networking, observability, and security.
• Experience building and operating enterprise-scale cloud platforms.
• Experience enabling AI/ML or Generative AI platforms within cloud environments.

Preferred Qualifications

• Experience building Internal Developer Platforms (IDP).
• Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, Vertex AI, OpenAI, or Anthropic.
• Knowledge of DevSecOps, SRE, Platform Engineering, and FinOps practices.
• Cloud certifications from AWS, Azure, or Google Cloud.