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# AI Developer - Python - GCP

- **Company:** Capgemini
- **Location:** Nashville, TN, United States
- **Salary:** $68,911.0 - $161,544.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, BigQuery, Cloud Computing, Cloud Engineering, Code Review, Encodings, Data Cleansing, Information Engineering, Data Masking, Data Security, Data Flow Control, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, SQL Databases, Enterprise Data Management, Google Cloud, Real Time Systems, Feature Engineering, Multi-Agent Systems, Model Validation, Generative AI, Agentic-AI, Data Strategy, Machine Learning Operations, Model Context Protocol, Data Pipelines
- **Published:** October 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=1080a11ce66b6817

## About the Role

* 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

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

Cloud & Infrastructure

 * Practical experience with:
 + Google Cloud Platform (GCP)
 + Google Cloud Storage (GCS)
 + BigQuery, 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.

## Description

1. 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.

 2. 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.

Your role

Operational Expectations (Soft Skills)

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.