Role Value Proposition The Manager DevOps & MLOps will provide technology leadership for building, scaling, and modernizing DevOps and MLOps capabilities across the Data & Analytics ecosystem.

The role will be responsible for defining and implementing DevOps and MLOps strategy, cloud engineering practices, CI/CD automation, ML deployment frameworks, platform engineering, containerization, and operational governance across on-premises and Azure environments.

The successful candidate will lead technical solutioning, drive engineering best practices, manage delivery and stakeholder relationships, and enable scalable deployment of Data, Analytics, AI/ML, and GenAI solutions into enterprise production environments.

This is a leadership role requiring a strong combination of technical depth, architecture/solutioning expertise, delivery leadership, stakeholder management, and team leadership.

Key Responsibilities

DevOps & MLOps Leadership

- Define and drive the DevOps and MLOps roadmap and strategy across the Data & Analytics organization.
- Lead the design, implementation, and modernization of CI/CD pipelines for Data, Analytics, AI/ML, and application workloads.
- Establish standardized DevOps and MLOps frameworks, reusable components, engineering standards, and deployment patterns.
- Drive automation across the complete ML lifecycle, including model development, validation, deployment, monitoring, retraining, and release management.
- Lead implementation of deployment pipelines for both batch and real-time ML models across on-premises and Azure environments.
- Drive adoption of Infrastructure as Code, automation, containerization, and platform engineering practices.
- Establish scalable and reusable deployment frameworks across multiple Data & Analytics teams.

Azure Cloud & Platform Engineering
- Provide technical leadership for Azure-based DevOps and MLOps platforms.
- Drive architecture and implementation across services including:

- Azure DevOps

- Azure Kubernetes Service (AKS)

- Azure Databricks

- Azure Synapse

- Azure ML

- Azure App Services

- Azure Key Vault

- Azure RBAC
- Lead hybrid cloud solutions spanning on-premises infrastructure and Azure cloud environments.
- Optimize cloud platforms for scalability, performance, security, reliability, and cost efficiency.
- Establish enterprise standards for cloud environments, deployment models, access management, and operational controls.

MLOps & AI/ML Engineering
- Lead the implementation of enterprise-grade MLOps capabilities supporting Data Science and AI/ML teams.
- Establish frameworks for model packaging, deployment, versioning, monitoring, governance, and lifecycle management.
- Enable productionization of machine learning and AI solutions through automated CI/CD and deployment pipelines.
- Provide technical leadership for MLflow, Azure ML and ML model serving/monitoring frameworks.
- Partner with Data Scientists, Data Engineers, Data Architects, and AI teams to transition models from experimentation to production.
- Drive adoption of emerging Generative AI, Agentic AI, and AI engineering practices within DevOps/MLOps platforms.

Containerization & Automation
- Lead enterprise adoption of Docker and Kubernetes/AKS for application, data, and ML workloads.
- Establish containerization and orchestration standards across the organization.
- Drive automation using Python, PowerShell, Bash, YAML, CLI and scripting frameworks.
- Develop reusable automation frameworks for infrastructure provisioning, application deployment, ML deployment,



and environment management.
- Promote Infrastructure as Code and automated setting provisioning practices.

Observability & Production Engineering
- Establish enterprise-level monitoring, logging, alerting, and observability frameworks for DevOps, Data, and ML workloads.
- Define operational KPIs and engineering standards for application and ML platform performance.
- Drive proactive identification and resolution of deployment, infrastructure, and model-performance issues.
- Ensure production platforms meet agreed standards for availability, scalability, security, and performance.
- Partner with engineering and operations teams to continuously improve production readiness.

Security, Governance & Compliance
- Embed security and governance controls throughout DevOps and MLOps pipelines.
- Ensure compliance with enterprise security, risk, governance, and regulatory standards.

- Drive implementation of

- RBAC

- Azure Key Vault

- CyberArk

- Secure secrets management

- Identity and access controls

- Secure CI/CD practices
- Establish DevSecOps practices across the development and deployment lifecycle.
- Ensure appropriate controls for ML models, data pipelines, cloud environments, and production deployments.

Technical Leadership & Solutioning
- Independently lead technical design, architecture, solutioning, estimation, and implementation planning.
- Review and approve technical designs, deployment architectures, automation frameworks, and cloud solutions.
- Identify opportunities for platform standardization, automation, modernization, and cost optimization.
- Provide technical mentorship and guidance to DevOps, MLOps, Cloud, Data Engineering, and Data Science teams.
- Drive engineering excellence and continuous improvement across the technology ecosystem.

People & Delivery Leadership
- Lead and mentor a team of DevOps/MLOps/Cloud engineers and technical professionals.
- Define technical objectives, development plans, and delivery priorities for the team.
- Manage delivery across multiple initiatives, ensuring quality, timelines, and business outcomes.
- Build a culture of automation, ownership, engineering excellence, and continuous learning.
- Support hiring, capability development, technical mentoring, and succession planning.
- Track delivery metrics, risks, dependencies, and resource requirements.

Stakeholder Management
- Collaborate extensively with stakeholders across:

- Business

- Global Technology
- Data & Analytics

- Data Engineering

- Data Science

- Data Governance

- Data Quality

- Data Architecture

- DevOps
- BI & Insights

- Operations

- Cybersecurity
- Act as a senior technology partner to global stakeholders and business leadership.
- Translate business requirements into scalable technical solutions.
- Communicate technical strategy, risks, opportunities, and delivery status to senior leadership.

Knowledge, Skills & Abilities

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or an equivalent educational qualification.

Experience

- 14+ years of overall IT experience, with significant experience in DevOps, MLOps,



Cloud Engineering, Platform Engineering, or related areas.
- Strong experience leading DevOps and MLOps transformation initiatives in large enterprise environments.
- Proven experience managing technical teams and delivering complex technology programs.
- Strong experience working across on-premises and Azure cloud environments.
- Experience working with global stakeholders and distributed technology teams.

Technical Skills DevOps & CI/CD Must Have
- Azure DevOps
- CI/CD pipeline architecture
- YAML
- Git / code versioning
- Release automation
- Deployment automation
- DevSecOps
- Infrastructure as Code
- Environment automation

MLOps Must Have
- ML model deployment and lifecycle management
- MLflow
- Azure ML
- Model serving and monitoring
- Batch and real-time ML deployment
- ML CI/CD
- Model versioning and governance
- Productionization of Data Science / AI solutions

Azure Strong Expertise
- Azure DevOps
- Azure Kubernetes Service (AKS)
- Azure Databricks
- Azure Synapse
- Azure ML
- Azure App Services
- Azure Key Vault
- Azure RBAC
- Azure CLI

Containerization & Orchestration
- Docker
- Kubernetes
- AKS
- Container lifecycle management
- Microservices deployment
- Container security

Programming & Scripting
- Python
- PowerShell
- Bash
- Shell scripting
- YAML
- CLI automation

Data & Big Data
- Apache Spark
- Hadoop
- Databricks
- SQL
- Data pipeline deployment and automation

APIs & Integration
- REST APIs
- HTTP / SSL
- JDBC
- XML
- Postman

Leadership Competencies
- Strong technical leadership and architecture capability
- Strategic thinking and technology roadmap development
- Strong stakeholder and partner management
- Excellent communication and presentation skills
- Structured problem-solving and analytical ability
- Strong delivery and execution orientation
- Ability to influence across global technology teams
- Team leadership, mentoring, and talent development
- Ability to manage multiple priorities and complex dependencies
- Strong understanding of enterprise governance, security, and compliance

Good to Have
- DevOps / Cloud certification such as Azure DevOps, Azure Solutions Architect, or equivalent
- Kubernetes certification
- Experience with Infrastructure as Code such as Terraform
- Experience with DevSecOps frameworks
- Exposure to CyberArk and enterprise access management
- Experience with RBAC and enterprise security controls
- Experience with Generative AI / Agentic AI platforms
- Experience building MLOps platforms for enterprise AI/ML teams
- Experience with FinOps / Azure cloud cost optimization
- Experience in large-scale Global Capability Center (GCC) environments

Ideal Candidate Profile The ideal candidate is a 14+ year technology leader with strong hands-on and leadership experience across DevOps, MLOps, Azure Cloud, CI/CD, Kubernetes, Docker, ML deployment, and platform engineering. The candidate should have demonstrated experience in leading DevOps/MLOps transformation, building scalable CI/CD platforms, enabling AI/ML productionization, managing engineering teams, and partnering with senior global stakeholders.

The role is best suited for professionals currently working as:

Manager DevOps | Senior Manager DevOps | DevOps Manager | MLOps Manager | MLOps Lead | Cloud & DevOps Manager | ML Platform Manager | DevOps/MLOps Architect | Cloud Engineering Manager | AI/ML Platform Lead

Core Focus

DevOps + MLOps + Azure Cloud + CI/CD + Kubernetes + ML Deployment + Platform Engineering + Technical Leadership

📌 Devops/MLOps - Manager (Pune)
🏢 Virtuoso Staffing Solutions
📍 Pune