Hiring GCP Platform Lead/Architect with

4 days ago

Bangalore Rural Bengaluru Pune, India VOIS Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Experience: 10-18years

Job Location and Work Mode: Pune/Bengaluru, Hybrid

Job Description

About this Role

At Vodafone, our strategic focus centres around three core pillars: Customer, Simplicity, and Growth. As we continue to strengthen our internal capabilities in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI, the role of an AI Cloud Platform Engineer becomes essential. This position supports our Technology department in driving innovation, enhancing customer experiences, and simplifying operations through advanced AI solutions.The AI Cloud Platform Engineer will be responsible for designing, developing, and deploying AI solutions on cloud platforms. The individual will collaborate with cross-functional teams to integrate AI capabilities into existing systems, while creating scalable, efficient, and secure AI infrastructure. This role plays a key part in enabling data-driven decision-making across Vodafone.

Who are you

You are a seasoned professional with over 7 years of experience in platform engineering, DevOps, or related fields. You bring deep expertise in cloud platforms, infrastructure automation, and AI/ML integration. You are passionate about innovation, committed to continuous improvement, and thrive in collaborative environments. Your approach is inclusive, proactive, and adaptable to dynamic business needs.

What you will do

  • Infrastructure Design & Maintenance: Build and maintain scalable, secure, and high-availability infrastructure on Google Cloud Platform (GCP).
  • Infrastructure as Code: Develop and manage Terraform modules, templates, and scripts to provision and manage GCP infrastructure at an enterprise level.
  • CI/CD Pipelines: Design and optimise CI/CD pipelines to support efficient and reliable data workload releases.
  • DevOps Engineering: Contribute to platform components as part of the DevOps team.
  • Automation & Efficiency: Implement Site Reliability Engineering (SRE) and DevSecOps practices to reduce manual tasks and improve automation.
  • Scripting & Monitoring: Create and maintain scripts for infrastructure automation, monitoring, and deployment.
  • Security Best Practices: Apply and enforce security standards across infrastructure and deployment processes.
  • AI/ML Integration: Collaborate with AI/ML teams to embed machine learning models into cloud infrastructure.
  • Data Services: Leverage GCP Data Services such as BigQuery, Dataproc, and Composer for data processing and analysis.

What skills you need

  • Cloud Platforms: Expertise in GCP (preferred), AWS, or Azure.
  • Programming Languages: Proficiency in Python, Java, NodeJS, and shell scripting.
  • AI/ML Frameworks: Experience with TensorFlow and PyTorch.
  • Infrastructure as Code: Advanced skills in Terraform.
  • DevOps Tools: Familiarity with CI/CD tools, especially GitHub Actions.
  • Security Management: Knowledge of GCP Secret Manager and enterprise security solutions.
  • Networking: Understanding of firewalls, ingress/egress patterns, and GCP networking.
  • Containerisation: Experience with Docker and Kubernetes.
  • Data Services: Working knowledge of BigQuery, Dataproc, and Composer.
  • Security Hardening: Experience with IAM, ACLs, and firewall rules on GCP.

What skills you will learn

  • Advanced integration of AI/ML models into cloud-native environments.
  • Enterprise-level automation and monitoring strategies.
  • Cross-functional collaboration with data science and engineering teams.
  • Implementation of inclusive and secure DevOps practices.
  • Exposure to cutting-edge GCP services and scalable infrastructure design.

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