AI Platform Engineer: Multi-Cloud AI & Data Platform

Greenberg Traurig; West Palm Beach (FL); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Greenberg Traurig is seeking an AI Platform Engineer to join the AI & Data Platform Enablement team, helping define reusable AI patterns and manage multi‑cloud AI deployments across Azure, AWS, and Google environments. You will establish RAG, vector strategies, and CI/CD pipelines, while collaborating with Security and Vendors to ensure compliant, scalable AI services.

Hybrid work options available; role reports to the Director of Enterprise Content and Cloud Services within a global law firm.

Qualifications

• Working knowledge of Azure AI Foundry/Azure OpenAI, AWS Bedrock, and/or Google Vertex AI model deployment and management.
• Familiarity with AI agent frameworks and the infrastructure required to run and govern agents in production.
• Proficiency with infrastructure-as-code (Terraform), containers (Docker, Kubernetes), and CI/CD pipelines.
• Strong scripting and development skills in Python, PowerShell, and/or other languages, including REST API design and integration.
• Solid understanding of cloud networking, identity, security, and cost-management fundamentals.
• Demonstrated ability to evaluate and manage third-party AI vendors and platform.
• Ability to communicate complex technical concepts clearly to technical and business audiences.
• Strong attention to detail with solid time and project management skills.
• Self-motivated, able to work independently, and comfortable operating in a shared services model.

Responsibilities

• Manages the firm’s AI control plane including deployment, versioning, and lifecycle of AI models across the firm’s multi‑cloud environments, including Microsoft Azure AI Foundry, AWS Bedrock, and Google Vertex AI
• Designs and manages the infrastructure supporting AI agents, including agent orchestration frameworks, runtime environments, and the controls around them
• Defines and maintains reusable AI architecture patterns including RAG, orchestration, prompt management, API design, and vector store strategies. Packages them as components solution teams can reuse
• Provides telemetry, logging, and audit data required for AI governance oversight
• Serves as a technical point of contact for AI platform vendors, partners, and internal teams in support of proofs of concept, integration, and operationalization
• Builds and maintains vector stores, embedding pipelines, and retrieval services used in AI solutions
• Establishes consistent CI/CD, environment, and infrastructure‑as‑code patterns for deploying and promoting AI workloads
• Collaborates with Information Security to ensure model deployments, agents, and platform services meet firm security, privacy, and compliance requirements
• Evaluates models, frameworks, and platform services across Azure, AWS, and GCP and recommends fit‑for‑purpose options balancing capability, cost, and risk
• Implements cost‑management and capacity practices for AI workloads across cloud providers
• Provides technical leadership, mentorship, and guidance to developers and solution teams
• Participates as a member of the AI Architectural Review Board to ensure AI solutions meet firm requirements
• Reviews existing AI implementations and recommends opportunities for better standardization, consolidation, or re‑architecture
• Authors and maintains platform documentation, reference architectures, and standard
• Creates and delivers technical presentations and training to technical and non‑technical audiences
• Appears on camera for meetings with colleagues and vendors
• Performs other duties as assigned by management

Skills

Azure AI Foundry / Azure OpenAI / AWS

AI agent frameworks

Terraform

Docker

Kubernetes

CI/CD

Python

REST API

Cloud security basics

Vendor evaluation

Technical communication

Time management

Self-motivation

Education

Bachelor’s degree in computer science, information technology, or equivalent

Azure/AWS/GCP AI certifications

Tools

Terraform

Docker

Kubernetes

CI/CD pipelines

Job description

Greenberg Traurig is seeking an AI Platform Engineer to join the AI & Data Platform Enablement team, helping define reusable AI patterns and manage multi‑cloud AI deployments across Azure, AWS, and Google environments. You will establish RAG, vector strategies, and CI/CD pipelines, while collaborating with Security and Vendors to ensure compliant, scalable AI services.

Hybrid work options available; role reports to the Director of Enterprise Content and Cloud Services within a global law firm.