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Vertex AI Engineer & Cloud Delivery Lead

ExperiencedNo visa sponsorship
Capgemini logo

at Capgemini

Consultancies

Posted 16 days ago

No clicks

**Vertex AI Engineer & Cloud Delivery Lead** lead AI/ML engineering and cloud delivery, design MLOps on Vertex AI, manage production-ready models. Key responsibilities include pipeline automation (Vertex AI Pipelines), model deployment and monitoring (Vertex AI Model Registry, Endpoints), featured engineering (Vertex AI Feature Store), GCP integrations (BigQuery, Dataflow), infrastructure management (Terraform), security (IAM, VPC Service Controls), cloud delivery & collaboration. Required: 4+ years GCP, 2+ years Vertex AI, Python proficiency, experience with ML frameworks, Terraform, IAM. Familiarity with GKE and containerization is beneficial. Drive adoption of GKE for custom model serving.

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
India

Full Job Description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

We are seeking an experienced Vertex AI Engineer and Cloud Delivery Lead to drive the design, deployment, and operationalisation of machine learning solutions on Google Cloud. This role bridges AI/ML engineering and cloud delivery, ensuring that models and pipelines reach production reliably, securely, and at scale.

Key Responsibilities:

  • Design and implement end-to-end MLOps pipelines on Vertex AI, including data ingestion, model training, evaluation, and deployment
  • Build and manage Vertex AI Pipelines (Kubeflow Pipelines) for automated model training and retraining workflows
  • Deploy and manage models using Vertex AI Model Registry, Endpoints, and Batch Prediction services
  • Implement feature engineering workflows using Vertex AI Feature Store
  • Develop GCP-native integrations connecting Vertex AI with BigQuery, Dataflow, Cloud Storage, and Pub/Sub
  • Manage infrastructure for ML workloads using Terraform, ensuring reproducible and version-controlled environments
  • Configure IAM policies for Vertex AI workloads including service account governance and VPC Service Controls
  • Lead cloud delivery activities: sprint planning, release management, environment promotion, and stakeholder communication
  • Establish model monitoring using Vertex AI Model Monitoring for data drift and skew detection
  • Collaborate with data scientists to containerise experiments and promote models through dev/staging/production
  • Drive adoption of GKE for model serving workloads where custom inference infrastructure is required

Your Profile

  • 4+ years of experience with GCP, including 2+ years hands-on with Vertex AI
  • Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Experience building Vertex AI Pipelines and managing model lifecycle in Vertex AI Model Registry
  • Solid Terraform skills for provisioning Vertex AI, GCS, BigQuery, and associated infrastructure
  • Good understanding of GCP IAM, particularly for securing ML pipelines and data access
  • Experience with GCP-native development patterns and event-driven architectures
  • Demonstrated cloud delivery experience including planning, execution, and stakeholder management
  • Familiarity with containerisation (Docker) and GKE for model serving

What you'll love about working here

  • You can shape your career with us. We offer a range of career paths and internal opportunities within Capgemini group. You will also get personalized career guidance from our leaders.
  • You will get comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage or new parent support via flexible work.
  • At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com

Vertex AI Engineer & Cloud Delivery Lead

Compensation

Not specified

City: Not specified

Country: India

Capgemini logo
Consultancies

16 days ago

No clicks

at Capgemini

ExperiencedNo visa sponsorship

**Vertex AI Engineer & Cloud Delivery Lead** lead AI/ML engineering and cloud delivery, design MLOps on Vertex AI, manage production-ready models. Key responsibilities include pipeline automation (Vertex AI Pipelines), model deployment and monitoring (Vertex AI Model Registry, Endpoints), featured engineering (Vertex AI Feature Store), GCP integrations (BigQuery, Dataflow), infrastructure management (Terraform), security (IAM, VPC Service Controls), cloud delivery & collaboration. Required: 4+ years GCP, 2+ years Vertex AI, Python proficiency, experience with ML frameworks, Terraform, IAM. Familiarity with GKE and containerization is beneficial. Drive adoption of GKE for custom model serving.

Full Job Description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

We are seeking an experienced Vertex AI Engineer and Cloud Delivery Lead to drive the design, deployment, and operationalisation of machine learning solutions on Google Cloud. This role bridges AI/ML engineering and cloud delivery, ensuring that models and pipelines reach production reliably, securely, and at scale.

Key Responsibilities:

  • Design and implement end-to-end MLOps pipelines on Vertex AI, including data ingestion, model training, evaluation, and deployment
  • Build and manage Vertex AI Pipelines (Kubeflow Pipelines) for automated model training and retraining workflows
  • Deploy and manage models using Vertex AI Model Registry, Endpoints, and Batch Prediction services
  • Implement feature engineering workflows using Vertex AI Feature Store
  • Develop GCP-native integrations connecting Vertex AI with BigQuery, Dataflow, Cloud Storage, and Pub/Sub
  • Manage infrastructure for ML workloads using Terraform, ensuring reproducible and version-controlled environments
  • Configure IAM policies for Vertex AI workloads including service account governance and VPC Service Controls
  • Lead cloud delivery activities: sprint planning, release management, environment promotion, and stakeholder communication
  • Establish model monitoring using Vertex AI Model Monitoring for data drift and skew detection
  • Collaborate with data scientists to containerise experiments and promote models through dev/staging/production
  • Drive adoption of GKE for model serving workloads where custom inference infrastructure is required

Your Profile

  • 4+ years of experience with GCP, including 2+ years hands-on with Vertex AI
  • Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Experience building Vertex AI Pipelines and managing model lifecycle in Vertex AI Model Registry
  • Solid Terraform skills for provisioning Vertex AI, GCS, BigQuery, and associated infrastructure
  • Good understanding of GCP IAM, particularly for securing ML pipelines and data access
  • Experience with GCP-native development patterns and event-driven architectures
  • Demonstrated cloud delivery experience including planning, execution, and stakeholder management
  • Familiarity with containerisation (Docker) and GKE for model serving

What you'll love about working here

  • You can shape your career with us. We offer a range of career paths and internal opportunities within Capgemini group. You will also get personalized career guidance from our leaders.
  • You will get comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage or new parent support via flexible work.
  • At Capgemini, you can work on cutting-edge projects in tech and engineering with industry leaders or create solutions to overcome societal and environmental challenges.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com