AI Platform Engineer – AI/ML & Generative AI

AI Platform Engineer – AI/ML & Generative AI

Location: Charlotte, NC – Onsite
Experience: 7+ Years

Job Overview

We are seeking an experiencedAI Platform Engineer / AI Engineer to design, build, and scaleAI/ML and enterprise-grade Generative AI solutions. The ideal candidate will have hands-on experience delivering AI solutions onGoogle Cloud Platform (GCP), with strong expertise inGemini Enterprise, Vertex AI, Python, RAG, Agentic AI, LLM applications, and production ML environments.

Key Responsibilities

• Design, develop, and deployAI/ML and Generative AI solutions for enterprise environments.
• Architect and implement solutions leveragingGemini Enterprise, including:
  • Gemini for Google Workspace
  • Enterprise AI Agents
  • Grounding
  • Search
• Build and productionizeML pipelines, APIs, and services using Python.
• Design and implement:
  • RAG architectures
  • Agentic workflows
  • LLM-based applications
  • AI agents
• Deploy, monitor, and optimize AI/ML models and services onGCP.
• Work withVertex AI, BigQuery, Cloud Run, GKE, Cloud Functions, and Pub/Sub.
• Collaborate with customers and stakeholders to gather requirements and translate business problems into scalable AI solutions.
• Ensure solutions meet enterprise standards forsecurity, scalability, performance, and cost efficiency.
• Partner with Data Engineering, MLOps, and Platform teams to integrate AI capabilities into existing systems.
• Stay current withVertex AI, Gemini models, Agent Builder, and Model Garden.
• Recommend appropriate GCP AI/ML technologies based on business requirements.
• Mentor junior engineers and contribute to AI/ML engineering best practices.

Required Qualifications

• 7+ years of experience in Software Engineering, AI Engineering, or ML Engineering.
• Hands-oncustomer-facing experience with Gemini Enterprise or equivalent enterprise GenAI platforms.
• Strong expertise inGoogle Cloud Platform (GCP), including:
  • Vertex AI
  • BigQuery
  • Cloud Run / GKE
  • IAM
  • Networking fundamentals
• AdvancedPython programming skills.
• Experience with AI/ML frameworks and libraries such as:
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • LangChain
  • LangGraph
• Strong understanding ofLLM fundamentals, including:
  • Prompt Engineering
  • Fine-tuning
  • Embeddings
  • Vector Databases
  • RAG
• Experience deploying and scalingML models in production environments.
• Strong understanding ofAPI design, microservices, and cloud-native architecture.
• Excellent communication skills with the ability to work directly with enterprise customers and stakeholders.

Preferred Qualifications

• GCP Professional certifications such as:
  • Professional Machine Learning Engineer
  • Professional Cloud Architect
  • Professional Data Engineer
• Experience withMLOps tools, including:
  • Vertex AI Pipelines
  • Kubeflow
  • MLflow
• Experience withAgentic AI frameworks and multi-agent orchestration.
• Experience inSolutions Architecture, Sales Engineering, or Pre-Sales Technical Consulting.
• Knowledge ofAI/ML data governance, security, compliance, and enterprise standards.

Core Skills

AI/ML | Generative AI | Agentic AI | Gemini Enterprise | GCP | Vertex AI | Python | RAG | LLM | LangChain | LangGraph | TensorFlow | PyTorch | Scikit-learn | Vector Databases | BigQuery | Cloud Run | GKE | Cloud Functions | Pub/Sub | IAM | MLOps | Vertex AI Pipelines | Kubeflow | MLflow | AI Agents | Model Garden | Agent Builder | APIs | Microservices | Cloud Architecture | AI Security | Data Governance