Technical Deployment Manager, AI Platform

Technical Deployment Manager, AI Platform

Description -

Job Summary

We are seeking an experienced Technical Deployment Manager, AI Platform to lead the end-to-end deployment of applications, AI/ML solutions, and cloud services onto our enterprise AI platform.

This role leads DevOps and Cloud Engineers responsible for moving projects from development through production deployment and operational readiness. The Technical Deployment Manager will own deployment planning, environment readiness, technical coordination, release execution, risk management, and transition to operations while ensuring solutions meet enterprise standards for security, reliability, compliance, and supportability.

The ideal candidate combines strong technical expertise in cloud infrastructure, DevOps, CI/CD, Kubernetes, Infrastructure as Code, automation, and SRE practices with proven engineering leadership and project delivery experience.

Key Responsibilities

Lead DevOps and Cloud Engineers supporting deployment of multiple projects onto the AI Platform.

Own the end-to-end deployment lifecycle, including planning, environment readiness, implementation, production release, validation, and operational handoff.

Translate project requirements into actionable infrastructure, DevOps, and deployment plans.

Develop deployment schedules, readiness criteria, dependency plans, rollback strategies, and production cutover plans.

Coordinate deployments across development, test, staging, and production environments.

Drive automation and reusable deployment patterns using CI/CD, Infrastructure as Code, containerization, and cloud-native technologies .

Partner with application, AI/ML, Platform Engineering, SRE, Security, Architecture, Governance, and Operations teams to resolve technical dependencies and deployment blockers.

Ensure production deployments meet security, compliance, change-management, monitoring, logging, support, and operational-readiness requirements.

Identify technical and delivery risks early, drive resolution, and provide clear status and escalation to project and platform leadership.

Lead deployment troubleshooting, rollback, recovery, and post-deployment reviews for critical releases.

Continuously improve deployment speed, reliability, quality, and operational efficiency through standardization and automation.

Required Qualifications

Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent experience.

Strong experience in DevOps, Cloud Engineering, SRE, Platform Engineering, Infrastructure Engineering, or technical deployment leadership .

Demonstrated experience leading engineers and delivering complex enterprise applications into production.

Strong experience with AWS and/or Microsoft Azure .

Hands-on knowledge of: Kubernetes and containerized workloads

CI/CD pipelines and release automation

Infrastructure as Code, such as Terraform

Git and source-control practices

Cloud infrastructure, networking, identity, and security.

Monitoring, logging, observability, and alerting

Production troubleshooting and incident management

Strong understanding of modern software development and deployment lifecycles.

Experience working within enterprise security, governance, compliance, and change-management processes.

Strong leadership, project management, problem-solving, and communication skills.

Preferred Qualifications

Experience deploying AI/ML, Generative AI, or Agentic AI solutions .

Experience supporting enterprise AI, cloud, or developer platforms.

Multi-cloud experience across AWS and Azure .

Experience with Kubernetes, Terraform, GitOps, and cloud-native architectures.

Knowledge of SRE principles, SLOs/SLIs, reliability engineering, and production operations.

Experience supporting business-critical applications in large enterprise environments.

AWS, Azure, Kubernetes, ITIL, or PMP certifications are a plus.

Cross-Org Skills

• Customer Centricity
• Prioritization
• Re