AI Platform Engineer – GenAI on GCP (On-site)

Capgemini; Charlotte (NC); On-site; USD 41,000 - 65,000; Full time

Job summary

Tundra Technical Solutions is seeking an AI Engineer to design, build, and scale AI/ML solutions for enterprise customers in Charlotte, NC. This on-site role focuses on generative AI deployments on Google Cloud Platform, including Gemini Enterprise.

You will develop production-grade ML pipelines, implement RAG architectures, and collaborate with data, MLOps, and platform teams to deliver secure and scalable solutions. 7+ years of experience and strong Python/GCP skills are required.

Qualifications

• 7+ years of experience in software/AI/ML engineering roles.
• Hands-on customer-facing experience with Gemini Enterprise.
• Advanced proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Strong understanding of LLM fundamentals and prompt techniques.
• Experience deploying ML models in production and API design.

Responsibilities

• Design, develop, and deploy AI/ML solutions for enterprise customers.
• Architect solutions using Gemini Enterprise and related AI agents.
• Build ML pipelines, APIs, and services in Python.
• Implement RAG architectures and agentic workflows.
• Deploy, monitor, and optimize models on GCP.
• Collaborate with customers to translate business problems into scalable AI solutions.
• Ensure security, scalability, and cost efficiency.
• Mentor junior engineers and share AI development best practices.

Skills

Python

TensorFlow

PyTorch

scikit-learn

LangChain

LangGraph

LLM concepts

API design

Cloud

Tools

Gemini Enterprise

Google Cloud Platform

Vertex AI

BigQuery

Cloud Run

GKE

Cloud Functions

Pub/Sub

Job description

Tundra Technical Solutions is seeking an AI Engineer to design, build, and scale AI/ML solutions for enterprise customers in Charlotte, NC. This on-site role focuses on generative AI deployments on Google Cloud Platform, including Gemini Enterprise.

You will develop production-grade ML pipelines, implement RAG architectures, and collaborate with data, MLOps, and platform teams to deliver secure and scalable solutions. 7+ years of experience and strong Python/GCP skills are required.