McDonald's

Runs and franchises fast-food restaurants

Sr Manager - Data Operations & Management

Platform EngineeringPosted on Nov 11

Full-timeHyderabad, Telangana, IndiaNo salary listed

About the Job

Requirements

At least 11 years of experience in AI/ML Platform Engineering, Cloud Platform Engineering, or Data & AI Platform development, preferably on Google Cloud Platform.
Strong expertise in Google Cloud Platform, including Vertex AI, BigQuery, Cloud Storage, Dataflow, Cloud Functions, Cloud Run, IAM, networking, and related platform services.
At least 5 years of experience designing, building, and managing enterprise-scale AI/ML platform capabilities, reusable services, and self-service enablement frameworks.
Experience implementing platform automation, Infrastructure as Code, preferably Terraform, CI/CD frameworks, and engineering standards for cloud-native platforms.
Experience with source code management, code quality, and engineering best practices using GitHub, GitHub Actions, pytest, SonarQube, or similar tools.
Experience developing platform services and integrations using Python and APIs.
Hands-on experience with AI/ML platform services such as Vertex AI Workbench, Model Registry, Feature Store, Vector Search, generative AI services, and platform enablement capabilities.
Experience with workflow orchestration and automation platforms such as Astronomer, Airflow, or similar technologies.
Strong knowledge of containerization and cloud-native technologies, including Docker, Kubernetes, and serverless architectures.
Experience establishing platform governance, access management, security controls, auditability, and compliance standards for AI/ML platforms.
Understanding of AI governance, responsible AI principles, and agent lifecycle governance, including onboarding, access management, deployment controls, and observability requirements.
Experience building reusable templates, accelerators, developer tooling, and self-service capabilities to improve platform adoption and engineering productivity.
Strong understanding of platform reliability, observability, scalability, availability, and operational readiness.
Ability to collaborate across Data Engineering, Data Science, Security, Infrastructure, Architecture, and business teams.

Responsibilities

Define and drive the AI/ML platform strategy, roadmap, and architecture.
Design scalable, secure, and reusable platform capabilities on Google Cloud Platform and Vertex AI.
Establish platform standards, reference architectures, and engineering best practices.
Evaluate and adopt emerging AI platform technologies.
Build and manage core AI/ML platform services, frameworks, and shared capabilities.
Develop reusable templates, accelerators, and automation solutions.
Enable standardized development and deployment patterns across AI teams.
Ensure platform scalability, reliability, and maintainability.
Define platform governance, onboarding standards, and guardrails.
Implement security, access management, compliance, and audit controls.
Establish governance for AI agents, models, APIs, and platform services.
Partner with Enterprise Architecture, Security, Risk, and Legal teams.
Deliver self-service capabilities for AI engineers and data scientists.
Create platform standards, documentation, and reusable assets.
Drive platform adoption and improve developer experience.
Promote consistent engineering practices across AI initiatives.
Establish platform monitoring, logging, alerting, and operational dashboards.
Drive reliability, resilience, performance, and capacity planning.
Define platform SLAs, SLOs, and operational readiness standards.
Partner with AI/ML Operations for production support readiness.
Lead AI/ML platform engineering initiatives and roadmap execution.
Mentor engineers and foster platform engineering best practices.
Collaborate with Data, AI, Security, Infrastructure, and Operations teams.
Communicate platform strategy, progress, risks, and outcomes to leadership.

About McDonald’s:

One of the world’s largest employers with locations in more than 100 countries, McDonald’s Corporation has corporate opportunities in Hyderabad. Our global offices serve as dynamic innovation and operations hubs, designed to expand McDonald's global talent base and in-house expertise. Our new office in Hyderabad will bring together knowledge across business, technology, analytics, and AI, accelerating our ability to deliver impactful solutions for the business and our customers across the globe.

Position Overview

Position Summary:

AI/ML Platform Lead

We are seeking an experienced AI & ML Platform Lead to drive the strategy, architecture, engineering, and enablement of enterprise AI/ML platform capabilities on Google Cloud Platform. This role is responsible for building and managing scalable AI/ML platform services, governance controls, development standards, self-service capabilities, and platform automation that enable Data Science and AI/ML Operations teams to rapidly build, deploy, and manage AI solutions securely and efficiently.

Key Responsibilities

Platform Strategy & Architecture

Define and drive the AI/ML platform strategy, roadmap, and architecture.
Design scalable, secure, and reusable platform capabilities on GCP and Vertex AI.
Establish platform standards, reference architectures, and engineering best practices.
Evaluate and adopt emerging AI platform technologies.

AI/ML Platform Engineering

Build and manage core AI/ML platform services, frameworks, and shared capabilities.
Develop reusable templates, accelerators, and automation solutions.
Enable standardized development and deployment patterns across AI teams.
Ensure platform scalability, reliability, and maintainability.

Platform Governance & Controls

Define platform governance, onboarding standards, and guardrails.
Implement security, access management, compliance, and audit controls.
Establish governance for AI agents, models, APIs, and platform services.
Partner with Enterprise Architecture, Security, Risk, and Legal teams.

Self-Service & Enablement

Deliver self-service capabilities for AI engineers and data scientists.
Create platform standards, documentation, and reusable assets.
Drive platform adoption and improve developer experience.
Promote consistent engineering practices across AI initiatives.

Platform Observability & Reliability

Establish platform monitoring, logging, alerting, and operational dashboards.
Drive reliability, resilience, performance, and capacity planning.
Define platform SLAs, SLOs, and operational readiness standards.
Partner with AI/ML Operations for production support readiness.

Leadership & Stakeholder Management

Lead AI/ML platform engineering initiatives and roadmap execution.
Mentor engineers and foster platform engineering best practices.
Collaborate with Data, AI, Security, Infrastructure, and Operations teams.
Communicate platform strategy, progress, risks, and outcomes to leadership.

Required Qualifications

11+ years of experience in AI/ML Platform Engineering, Cloud Platform Engineering, or Data & AI Platform development, preferably on GCP.
Strong expertise in Google Cloud Platform (GCP), including Vertex AI, BigQuery, Cloud Storage, Dataflow, Cloud Functions, Cloud Run, IAM, Networking, and related platform services.
5+ years of experience designing, building, and managing enterprise-scale AI/ML platform capabilities, reusable services, and self-service enablement frameworks.
Experience implementing platform automation, Infrastructure as Code (Terraform preferred), CI/CD frameworks, and engineering standards for cloud-native platforms.
Strong experience with source code management, code quality, and engineering best practices using GitHub, GitHub Actions, pytest, SonarQube, or similar tools.
Experience developing platform services and integrations using Python and APIs.
Hands-on experience with AI/ML platform services such as Vertex AI Workbench, Model Registry, Feature Store, Vector Search, Generative AI services, and platform enablement capabilities.
Experience with workflow orchestration and automation platforms such as Astronomer, Airflow, or similar technologies.
Strong knowledge of containerization and cloud-native technologies, including Docker, Kubernetes, and serverless architectures.
Experience establishing platform governance, access management, security controls, auditability, and compliance standards for AI/ML platforms.
Understanding of AI governance, responsible AI principles, and agent lifecycle governance, including onboarding, access management, deployment controls, and observability requirements.
Experience building reusable templates, accelerators, developer tooling, and self-service capabilities to improve platform adoption and engineering productivity.
Strong understanding of platform reliability, observability, scalability, availability, and operational readiness.
Excellent stakeholder management and communication skills, with the ability to collaborate effectively across Data Engineering, Data Science, Security, Infrastructure, Architecture, and business teams.

Why Join Us:

Work with a mission-driven team building cutting-edge technology. Be part of a collaborative, inclusive, and growth-oriented culture.

Work location: Hyderabad, India

Work hours: Regular

Work pattern: Full time role.

Work mode: Hybrid.

McDonald’s is the world’s leading global foodservice retailer with over 40,000 locations in over 100 countries. Approximately 95% of McDonald’s restaurants worldwide are owned and operated by independent local business owners. At McDonald’s, we lead through our values centered on inclusivity, service, integrity, community, and family. Here is your chance to get in on something special as we grow our corporate team in India and allow you to grow your career.

About the Company

McDonald's

Runs and franchises fast-food restaurants

McDonald's runs and franchises quick-service restaurants for customers seeking burgers, chicken, fries, breakfast food and coffee. Its menu includes the Big Mac and Chicken McNuggets, while customers order at counters, drive-throughs, self-service kiosks and through its mobile app. Independent operators run most locations under agreements that license the brand and restaurant system. The corporation earns money from its own restaurant sales and from franchise royalties, rent and initial fees, with conventional franchise sites supported by property it owns or leases. The modern business dates to Ray Kroc's McDonald's System in 1955 and is headquartered in Chicago, Illinois.

Company size: 10,001+
Company stage: IPO
Headquarters: Chicago, IL
Founded: 1955

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