GCP Data & AI Architect

About Xebia

With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition.

We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Functional Programming, Low Code, and Microsoft.

We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services.

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Overview

The GCP Data & AI Architect will lead Tech Presales associated with the design and delivery of cloud-native data and AI solutions offerings across industries and geographies. The role involves leading existing and prospect customer discussions on defining scalable architectures, ensuring compliance and security, and driving innovation through advanced analytics, machine learning, and generative AI capabilities on GCP. The architect acts as a trusted advisor to clients and internal teams, guiding them through every stage of their GCP data and AI journey.

Key Responsibilities

1. Solution Architecture and Design

• Design end-to-end GCP data and AI architectures, including data ingestion, storage, processing, analytics, and ML deployment.


• Architect and implement data lakes, lakehouses, and data warehouses using GCP services such as BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub.


• Define AI/ML pipelines leveraging Vertex AI, AI Platform, TensorFlow, and AutoML for scalable model training and deployment.


• Integrate data governance, lineage, and observability frameworks using Data Catalog, Dataplex, and Cloud Composer.


• Develop reference architectures, blueprints, and best practices for GCP-based data and AI solutions across global delivery teams.

2. Data Engineering and Platform Modernization

• Lead data modernization initiatives, migrating on-premise or legacy data systems to GCP.


• Design real-time and batch data pipelines using Dataflow (Apache Beam) and Pub/Subfor streaming analytics.


• Optimize BigQuery performance and cost efficiency through partitioning, clustering, and query optimization.


• Collaborate with DevOps teams to automate infrastructure provisioning using Terraform, Deployment Manager, or Cloud Build.


• Ensure data quality, reliability, and scalability across all data layers.

3. AI and Machine Learning Integration

• Architect AI/ML solutions using Vertex AI pipelines, integrating with BigQuery ML and TensorFlow Extended (TFX) for production-grade deployments.


• Implement MLOps frameworks for continuous integration, delivery, and monitoring of ML models.


• Develop custom AI solutions for NLP, computer vision, predictive analytics, and generative AI use cases.


• Collaborate with data scientists to operationalize models and ensure explainability, fairness, and compliance.


• Integrate AI models into enterprise applications using APIs, Cloud Functions, and microservices architectures.

4. Governance, Security, and Compliance

• Define and enforce data governance and security frameworks aligned with corporate and regulatory standards (GDPR, HIPAA, CCPA).


• Implement IAM policies, VPC Service Controls, and encryption mechanisms to ensure data protection.


• Establish AI governance frameworks for model lifecycle management, bias detection, and ethical AI practices.


• Conduct architecture reviews and compliance assessments to ensure adherence to GCP best practices and client requirements.

5. Client Engagement and Technical Leadership

• Partner with client executives and technical stakeholders to define data and AI strategieson GCP.


• Lead discovery workshops, architecture assessments, and proof-of-concept (POC)engagements.


• Support pre-sales activities, including RFP responses, solution proposals, and technical presentations.


• Provide technical leadership to global delivery teams, ensuring consistent architecture implementation.


• Act as a GCP evangelist, promoting adoption of cloud-native AI and data analytics capabilities.

6. Innovation and Continuous Improvement

• Stay updated on GCP product releases, AI research, and industry trends to drive innovation.


• Develop accelerators, reusable assets, and frameworks to enhance delivery efficiency.


• Mentor engineers and architects, building organizational capability in GCP data and AI technologies.


• Collaborate with Google Cloud’s partner ecosystem for joint go-to-market and innovation initiatives.

Required Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.


• Experience: 10+ years in data and AI architecture, with at least 5 years focused on GCP solutions in enterprise or SI environments.


• Certifications (Preferred):




• Google Cloud Professional Data Engineer


• Google Cloud Professional Machine Learning Engineer


• Google Cloud Professional Cloud Architect


• Technical Expertise:




• Data Services: BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Dataplex, Data Catalog


• AI/ML Services: Vertex AI, AI Platform, TensorFlow, AutoML, BigQuery ML


• Integration & Orchestration: Cloud Composer, Cloud Functions, Cloud Run, API Gateway


• Infrastructure: GKE, Terraform, Cloud Build, IAM, VPC, Cloud Security Command Center


• Programming: Python, SQL, Java, Scala


• MLOps Tools: MLflow, Kubeflow, TFX, CI/CD pipelines


• Soft Skills: Strong client communication, stakeholder management, and cross-functional collaboration abilities.

Performance Metrics

Category

Key Performance Indicators (KPIs)

Scalability, performance, and cost optimization of GCP solutions

On-time delivery, client satisfaction, and project success rate

Number of reusable GCP assets, accelerators, or IP created

Reduction in data processing costs and latency

GCP audit compliance, data protection adherence

Number of team members trained or certified on GCP

Benefits

• Medical, Dental and Vision Insurance (Subsidized)


• Flexible Spending Accounts (Healthcare and Dependent Care)


• Short-Term and Long-Term Disability


• Life and AD&D Insurance


• Assistance Program


• Matched 401(k) Retirement Savings Plan


• Paid Time Off

While the talent scarcity within IT is at an all-time high and still growing, Xebia sticks to the mission of “aiming for thought leadership”, thus working with the best professionals in the market.

At Xebia, you will get the chance to work with passionate professionals within their field of expertise. We offer more than just a job, we offer a career. We are looking forward to working with you!

Xebia is committed to creating an inclusive and diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Please feel free to share your preferred pronouns with us during the application process.

All persons hired will be required to verify identity and eligibility to work in North America, and to complete any required employment eligibility forms.