Agentic AI Engineer

Capgemini; Nashville (TN); Hybrid; USD 69,000 - 162,000; Full time

Benefits offered by this job

Medical coverage

401(k)

PTO 12-25 days

Life insurance

Employee assistance

Job summary

Capgemini is seeking a hybrid-role AI/ML engineer to design and build agentic AI systems on Google Cloud. You will implement solutions using Vertex AI tools, connect to BigQuery and Cloud Spanner, and develop real-time data pipelines with Dataflow.

The role emphasizes end-to-end problem solving, multi-agent architectures, and production-grade data workflows. A strong background in Python, SQL, and GCP is required.

Qualifications

• Strong experience with Vertex AI and related tools.
• Hands-on GCP work with BigQuery, Cloud Storage, and Spanner.
• Experience in data preprocessing and model deployment.
• Knowledge of multi-agent architectures and real-time processing.

Responsibilities

• Design and build agentic AI systems to automate business processes.
• Develop multi-agent systems for end-to-end problem solving.
• Integrate AI agents with enterprise data sources (BigQuery, Spanner).
• Design and optimize AI/ML solutions on Vertex AI, including training and deployment.
• Build real-time and batch data pipelines using Dataflow and Vertex AI Endpoints.

Skills

Multi-agent systems

Agentic architectures

Real-time processing

Python

SQL (BigQuery)

Tools

Vertex AI

Vertex AI Agent Builder

Model Garden

Vertex AI Pipelines

BigQuery

Cloud Spanner

MCP Toolbox

Vertex Endpoints

BigQuery Vector Search

AlloyDB

Dataflow

Python

SQL (BigQuery)

Job description

In this hybrid role, you will design and build agentic AI systems that automate business processes and support end-to-end problem solving. The position focuses on implementing solutions on Google Cloud, including Vertex AI-based agent development, RAG and vector search, and production data pipelines.

Key Responsibilities

• Build intelligent AI agents using Vertex AI Agent Builder and ADK to automate business processes.
• Develop and manage multi-agent systems for end-to-end problem solving.
• Integrate AI agents with enterprise data sources, including BigQuery and Cloud Spanner, using MCP Toolbox.
• Design and optimize AI/ML solutions on Vertex AI, covering model training, tuning, deployment, and evaluation.
• Build real-time and batch data pipelines using Dataflow and Vertex AI Endpoints.
• Implement RAG and vector search solutions using BigQuery Vector Search or AlloyDB.

Required Qualifications

• Strong experience with Vertex AI, Vertex AI Agent Builder, Model Garden, and Vertex AI Pipelines.
• Proficiency in Python and SQL (BigQuery), along with data preprocessing techniques.
• Hands-on experience with GCP, including BigQuery, Cloud Storage, Vertex AI Endpoints, and Cloud Spanner.
• Knowledge of multi-agent systems, agentic architectures, and real-time processing.

Technologies

• Vertex AI, Vertex AI Agent Builder, ADK
• MCP Toolbox
• BigQuery, Cloud Spanner
• Vertex AI Pipelines, Model Garden
• Python, SQL (BigQuery)
• GCP, Cloud Storage, Vertex AI Endpoints
• Dataflow
• RAG, BigQuery Vector Search, AlloyDB

Compensation

USD 68,911 - 161,544 per year.

Location

Nashville, TN (Hybrid). This position is a hybrid role based out of Chicago, Atlanta, Nashville, Dallas, New Jersey.

Benefits

• Paid time off based on employee grade (A-F): Vacation 12-25 days, 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

Preferred Qualification

• Experience in Financial Services or Retail domains.
• Familiarity with credit risk, forecasting, search/recommendation systems, and AI governance.
• Knowledge of PII protection, data masking, and compliance standards.