AI Platform Engineer

Greenberg Traurig (GT), a global law firm with locations across the world in 15 countries, has an exciting employment opportunity for you. We offer competitive compensation and an excellent benefits package, along with the opportunity to work within an innovative and collaborative environment. Join our Technology Team as an AI Platform Engineer located in various offices. We are seeking a professional who thrives in a fast-paced, deadline-driven environment. The ideal candidate possesses strong problem-solving and decision-making abilities, ensuring efficiency and accuracy in every task. With a dedicated work ethic and a can-do attitude, you will take initiative and approach challenges with confidence and resilience. Excellent communication skills are essential for collaborating effectively across teams and delivering exceptional client service. If you are someone who demonstrates initiative, adaptability, and innovation, we invite you to join our team. This role can be based in various offices, on a hybrid basis. This role reports to the Director of Enterprise Content and Cloud Services. Position Summary The AI Platform Engineer is a member of the AI & Data Platform Enablement team responsible for defining the firm’s reusable AI patterns and managing the multi-cloud platform on which AI solutions are built and deployed. This role owns the deployment and lifecycle management of AI models across the firm’s Microsoft Azure AI Foundry, AWS Bedrock, and Google Vertex AI environments and establishes standards for retrieval-augmented generation (RAG), orchestration, APIs, and vector strategies. The AI Platform Engineer also manages the infrastructure that supports AI agents, including agent frameworks and associated vendor platforms. The AI Platform Engineer collaborates with Cloud Services, AI Development, Information Security, and third-party vendors to ensure AI is built once and reused consistently across the firm. Key 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 AIDesigns and manages the infrastructure supporting AI agents, including agent orchestration frameworks, runtime environments, and the controls around themDefines and maintains reusable AI architecture patterns including RAG, orchestration, prompt management, API design, and vector store strategies. Packages them as components solution teams can reuseProvides telemetry, logging, and audit data required for AI governance oversightServes as a technical point of contact for AI platform vendors, partners, and internal teams in support of proofs of concept, integration, and operationalizationBuilds and maintains vector stores, embedding pipelines, and retrieval services used in AI solutionsEstablishes consistent CI/CD, environment, and infrastructure-as-code patterns for deploying and promoting AI workloadsCollaborates with Information Security to ensure model deployments, agents, and platform services meet firm security, privacy, and compliance requirementsEvaluates models, frameworks, and platform services across Azure, AWS, and GCP and recommends fit-for-purpose options balancing capability, cost, and riskImplements cost-management and capacity practices for AI workloads across cloud providersProvides technical leadership, mentorship, and guidance to developers and solution teamsParticipates as a member of the AI Architectural Review Board to ensure AI solutions meet firm requirementsReviews existing AI implementations and recommends opportunities for better standardization, consolidation, or re-architectureAuthors and maintains platform documentation, reference architectures, and standardCreates and delivers technical presentations and training to technical and non-technical audiencesAppears on camera for meetings with colleagues and vendorsPerforms other duties as assigned by management Qualifications Skills & Competencies Working knowledge of Azure AI Foundry/Azure OpenAI, AWS Bedrock, and/or Google Vertex AI model deployment and managementFamiliarity with AI agent frameworks and the infrastructure required to run and govern agents in productionProficiency with infrastructure-as-code (Terraform), containers (Docker, Kubernetes), and CI/CD pipelinesStrong scripting and development skills in Python, PowerShell, and/or other languages, including REST API design and integrationSolid understanding of cloud networking, identity, security, and cost-management fundamentalsDemonstrated ability to evaluate and manage third-party AI vendors and platformAbility to communicate complex technical concepts clearly to technical and business audiencesStrong attention to detail with solid time and project management skillsSelf-motivated, able to work independently, and comfortable operating in a shared services model Education & Prior Experience Bachelor’s degree in computer science, information technology, or equivalent practical experience7+ years of experience in platform engineering, cloud solutions, or machine learning/AI engineering roles3+ years of hands-on experience deploying or operating AI/ML workloads in a major cloud environmentDemonstrated experience with multi-cloud platforms (Azure, AWS, GCP) and AI model deploymentStrong hands-on experience deploying and managing AI/ML or large language models in at least one major cloud (Azure, AWS, or GCP); multi-cloud experience strongly preferredExperience designing AI architecture patterns including RAG, orchestration frameworks (e.g., Semantic Kernel, LangChain), and vector databasesCertifications in Azure, AWS, GCP, or AI/ML specialties preferredExperience working in a professional services organization strongly preferred. Law firm experience a plus GT is an EEO employer with an inclusive workplace committed to merit-based consideration and review without regard to an individual’s race, sex, or other protected characteristics and to the principles of non-discrimination on any protected basis.