AI/ML Engineer - Agentic AI & Vertex AI

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

About the role

At Capgemini, you will collaborate with cross-functional teams to deliver innovative technology solutions that drive business value and enhance client experiences. You will contribute to the design, development, and continuous improvement of scalable, high-quality solutions in a dynamic and collaborative environment.

Responsibilities

• Agentic AI Design & Implementation
  • Design and develop intelligent AI agents using Vertex AI Agent Builder to automate complex business processes and workflows.
  • Leverage the Agent Development Kit (ADK) to build, orchestrate, and manage multi-agent systems capable of collaborating on end-to-end business challenges.
  • Implement and integrate Model Context Protocol (MCP) Toolbox to securely connect AI agents with enterprise data platforms such as BigQuery and Cloud Spanner.
  • Architect scalable agentic solutions that effectively combine reasoning, retrieval, tool usage, and workflow automation.
• AI-Driven Data Strategy & Engineering
  • Utilize Vertex AI for model training, fine-tuning, evaluation, and deployment, while integrating seamlessly with BigQuery for feature engineering and analytics.
  • Build and optimize real-time and batch data pipelines using services such as Dataflow to support large-scale AI and ML workloads.
  • Enable low-latency inference through Vertex AI Endpoints and RunInference APIs for production-grade AI applications.
  • Implement retrieval-augmented architectures using vector search capabilities within BigQuery and AlloyDB, ensuring AI systems remain grounded in current business context and reducing knowledge drift.
• Operational Expectations (Soft Skills)
  • Active Participation
    • Attend internal and customer-facing meetings punctually and consistently.
    • Remain actively engaged in technical discussions, reviews, and planning sessions.
  • Transparent Communication
    • Provide regular, structured updates on project progress, milestones, risks, and technical blockers.
    • Communicate effectively with both technical teams and business stakeholders.
  • Proactive Collaboration
    • Seek guidance when encountering challenges and contribute to a collaborative problem-solving culture.
    • Support peers through knowledge sharing, code reviews, and troubleshooting efforts.
  • Consultative Mindset
    • Work closely with stakeholders to translate business objectives into scalable and maintainable technical solutions.
    • Navigate complex enterprise environments and align AI initiatives with organizational goals.

Requirements

• Vertex AI Expertise
  • Strong hands-on experience with:
  • Vertex AI Model Garden
  • Vertex AI Pipelines
  • Model Evaluation and Optimization
  • Vertex AI Endpoints
  • Vertex AI Agent Builder
• Data & Machine Learning Engineering
  • Advanced proficiency in SQL (BigQuery) and Python for machine learning and data engineering.
  • Experience with:
  • Data preprocessing and feature engineering
  • Data scaling and normalization
  • Encoding techniques
  • Missing value imputation
  • Model performance monitoring
• Cloud & Infrastructure
  • Practical experience with:
  • Google Cloud Platform (GCP)
  • Google Cloud Storage (GCS)
  • BigQuery
  • Cloud Spanner
  • Vertex AI Endpoints
• Emerging AI Technologies
  • Understanding of modern agentic AI architectures and multi-agent systems.
  • Familiarity with stateful real-time processing, contextual memory, retrieval systems, and AI orchestration frameworks.
  • Knowledge of current trends and innovations in Generative AI and autonomous agents.

Preferred Qualifications

• Experience in Financial Services, Banking, FinTech, or Retail domains.
• Understanding of industry-specific use cases such as:
• Credit Risk Assessment
• Fraud Detection
• Royalty Forecasting
• Search Relevance Optimization
• Customer Intelligence Platforms
• Knowledge of data privacy, governance, and regulatory compliance.
• Experience implementing PII protection, including:
• Data masking
• Data redaction
• Secure data handling practices
• Compliance-driven AI architectures

Ideal Candidate Profile

A highly collaborative AI/ML professional with deep expertise in Vertex AI, BigQuery, agentic architectures, and cloud-native machine learning, capable of designing enterprise-grade AI solutions that transform business requirements into scalable, secure, and production-ready systems.

Pay

The base compensation range for this role in the posted location is $53,580 to $122,400. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Benefits

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• Paid time off based on employee grade (A-F), defined by policy:
• Vacation: 12-25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility