AI Platform Engineer

The AI Platform Engineer joins Greenberg Traurig’s AI & Data Platform Enablement team to manage the multi-cloud platform used to build and deploy AI solutions. Reporting to the Director of Enterprise Content and Cloud Services, the engineer defines reusable architecture patterns and manages AI model deployment and lifecycle across Microsoft Azure AI Foundry, AWS Bedrock, and Google Vertex AI. The role is hybrid and can be based in various firm offices.

Responsibilities

• Manage the AI control plane, including model deployment, versioning, and lifecycle management. Design the infrastructure, runtime environments, orchestration frameworks, and controls supporting AI agents.
• Define reusable patterns for retrieval-augmented generation, orchestration, prompt management, APIs, and vector stores. Build vector stores, embedding pipelines, and retrieval services.
• Establish CI/CD, environment, and infrastructure-as-code practices for AI workloads. Provide telemetry, logging, and audit data for governance; work with Information Security on security, privacy, and compliance.
• Evaluate cloud models, frameworks, and services for capability, cost, and risk; manage workload costs and capacity. Support vendors and internal teams with proofs of concept and integration, review implementations, mentor developers, participate in architectural review, and produce documentation and technical training.

Qualifications

• Bachelor’s degree in computer science or information technology, or equivalent practical experience. At least 7 years in platform engineering, cloud solutions, or machine learning/AI engineering, including at least 3 years deploying or operating AI/ML workloads in a major cloud environment.
• Experience with AI model deployment, multi-cloud platforms, RAG architecture, orchestration frameworks such as Semantic Kernel or LangChain, and vector databases. Working knowledge of Azure AI Foundry/Azure OpenAI, AWS Bedrock, and/or Google Vertex AI; familiarity with production AI agent infrastructure.
• Proficiency with Terraform, Docker, Kubernetes, CI/CD, scripting in Python, PowerShell, and/or other languages, and REST API design and integration. Understanding of cloud networking, identity, security, and cost management; ability to manage AI vendors and communicate with technical and business audiences.

Preferred

Strong multi-cloud experience; Azure, AWS, GCP, or AI/ML certifications; professional-services experience. Law firm experience is a plus. The posting mentions competitive compensation and a benefits package but gives no salary amount.