AI/ML Engineer - Agentic AI & Vertex AI

Capgemini•Atlanta, GA

4d•$53,580 - $122,400•Remote

About The Position

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.

Requirements

Strong hands-on experience with Vertex AI Model Garden
Strong hands-on experience with Vertex AI Pipelines
Strong hands-on experience with Model Evaluation and Optimization
Strong hands-on experience with Vertex AI Endpoints
Strong hands-on experience with Vertex AI Agent Builder
Advanced proficiency in SQL (BigQuery) and Python for machine learning and data engineering.
Experience with Data preprocessing and feature engineering
Experience with Data scaling and normalization
Experience with Encoding techniques
Experience with Missing value imputation
Experience with Model performance monitoring
Practical experience with Google Cloud Platform (GCP)
Practical experience with Google Cloud Storage (GCS)
Practical experience with BigQuery
Practical experience with Cloud Spanner
Practical experience with Vertex AI Endpoints
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.

Nice To Haves

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

Responsibilities

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.
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.
Attend internal and customer-facing meetings punctually and consistently.
Remain actively engaged in technical discussions, reviews, and planning sessions.
Provide regular, structured updates on project progress, milestones, risks, and technical blockers.
Communicate effectively with both technical teams and business stakeholders.
Seek guidance when encountering challenges and contribute to a collaborative problem-solving culture.
Support peers through knowledge sharing, code reviews, and troubleshooting efforts.
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.