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 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

Qualifications

Skills & Competencies

• 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

Education & Prior Experience

• Bachelor’s degree in computer science, information technology, or equivalent practical experience
• 7+ years of experience in platform engineering, cloud solutions, or machine learning/AI engineering roles
• 3+ years of hands-on experience deploying or operating AI/ML workloads in a major cloud environment
• Demonstrated experience with multi-cloud platforms
• (Azure, AWS, GCP) and AI model deployment
• Strong 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 preferred
• Experience designing AI architecture patterns including RAG, orchestration frameworks (e.g., Semantic Kernel, LangChain), and vector databases
• Certifications in Azure, AWS, GCP, or AI/ML specialties preferred
• Experience working in a professional services organization strongly preferred. Law firm experience a plus