Agentic AI Engineer

The Agentic AI Engineer is responsible for designing, developing, and deploying advanced AI agent systems and intelligent applications that drive strategic transformation across the firm. This role is centered on building autonomous, multi-step AI workflows and chatbot solutions that leverage large language models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and agentic frameworks—with a primary focus on Microsoft Copilot Studio and Azure AI services.

Reporting to Enterprise Applications leadership within the Technology and Data Services department, the Agentic AI Engineer serves as the firm’s foremost technical expert on AI agent design—collaborating with attorneys, practice groups, and business units to translate complex legal and operational needs into scalable, secure, and governed AI solutions within the Microsoft 365 and cloud ecosystem. For the full jobdescription, please click on the More Info icon.

Duties and Responsibilities

Primary Responsibilities

• Design, develop, and deploy AI chatbots and autonomous agents using Microsoft Copilot Studio and Power Automate, enabling intelligent, multi-turn conversational experiences and self-directing workflows for legal and administrative use cases.
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines that connect LLMs to the firm’s authoritative data sources—including NetDocuments, SharePoint, and internal knowledge bases—to deliver accurate, context-aware AI responses grounded in firm content.
• Build and manage AI agent frameworks that support multi-agent orchestration, tool-calling, memory, and reasoning patterns; design agents capable of autonomous decision-making across complex, multi-step legal workflows.
• Integrate Large Language Models (LLMs) with enterprise data and systems—including Microsoft 365, NetDocuments, CRM platforms, and practice management systems—ensuring seamless, secure, and well-governed data flows between AI agents and source-of-truth systems.
• Develop and deploy AI solutions leveraging Azure AI services (Azure AI Foundry, Azure OpenAI, Azure AI Search), selecting the appropriate service and configuration based on capability fit, security posture, and firm requirements.
• Collaborate with attorneys, practice groups, and business stakeholders to identify AI agent use cases; translate ambiguous business requirements into clearly defined agent architectures, success criteria, and phased delivery roadmaps.
• Design and manage the full AI agent development lifecycle—from prompt engineering and LLM selection through RAG pipeline construction, agent testing, and production deployment—ensuring solutions are reliable, auditable, and aligned with governance standards.
• Establish and enforce AI governance standards for agentic systems, including access controls, model versioning, output guardrails, bias mitigation, and compliance with attorney-client privilege and data privacy obligations.
• Evaluate emerging AI agent frameworks, foundation models, and orchestration platforms; prototype and recommend tools based on fit with the firm’s technology ecosystem and security requirements.
• Design and run structured pilot programs for new AI agent solutions, defining measurable success criteria, feedback mechanisms, and go/no-go frameworks to guide production adoption decisions.
• Develop and maintain comprehensive technical documentation for all AI agent solutions—including architecture diagrams, agent flow maps, RAG pipeline references, prompt libraries, and end-user guides.
• Monitor deployed AI agents and RAG systems for performance, accuracy, reliability, and compliance; proactively implement improvements and respond to production issues as needed.
• Promote responsible AI use across the firm by ensuring all agentic solutions adhere to data governance policies, privacy standards, and applicable legal industry regulations.
• Provide guidance and enablement to attorneys and staff on adopted AI agent tools, fostering a culture of responsible AI adoption and innovation.

Secondary

• Performs other duties as assigned.

Minimum Qualifications

Education

• Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, or a related field preferred; equivalent practical experience considered.

Experience

• 3–5+ years of experience in AI/ML engineering, software engineering, or applied AI development, with demonstrated hands-on work building LLM-based applications, AI agents, or RAG systems. Experience in a law firm, professional services, or similarly regulated environment preferred.

Special Knowledge

• Deep, hands-on knowledge of LLM concepts: prompt engineering, few-shot and chain-of-thought techniques, fine-tuning strategies, and retrieval-augmented generation (RAG) architectures.
• Strong working knowledge of AI agent frameworks and orchestration layers, including Microsoft Copilot Studio agent capabilities and equivalent open-source or commercial platforms; ability to evaluate and adopt new frameworks as the landscape evolves.
• Experience designing and building multi-agent systems with tool-calling, memory management, reasoning loops, and guardrails for production-grade reliability.
• Familiarity with AI infrastructure concepts: vector databases (e.g., Azure AI Search, Pinecone, Chroma), embedding pipelines, chunking strategies, and retrieval optimization for RAG.
• Working knowledge of Azure AI services (Azure OpenAI, Azure AI Foundry, Azure AI Search) for agentic solution development, including environment provisioning, API governance, and integration with enterprise systems.
• Understanding of data governance, privacy, and compliance requirements in the context of AI agents, including attorney-client privilege, data residency, and confidentiality obligations.

Technical Skills

• Proficiency in Python and/or JavaScript/TypeScript for AI application development, LLM API integration, and agentic workflow construction.
• Demonstrated experience integrating LLM APIs—including Azure OpenAI, Anthropic Claude, and OpenAI—into enterprise applications and business workflows.
• Hands-on experience building chatbot and agent solutions in Microsoft Copilot Studio, including custom connectors, topics, actions, and Power Automate integration.
• Strong working knowledge of the Microsoft 365 ecosystem—Power Platform, SharePoint, Teams, and Graph API—and their integration with AI agents and LLM services.
• Experience designing and implementing RAG pipelines: document ingestion, chunking, embedding, vector indexing, and retrieval-augmented response generation.
• Proficiency with RESTful APIs and web services for AI system integration, data access, and enterprise application connectivity.
• Experience with source control systems (Azure DevOps, GitHub) and CI/CD practices for versioning, testing, and deploying AI agent solutions.
• SQL proficiency for data querying and extraction in support of AI solution development.
• Familiarity with Azure cloud infrastructure concepts relevant to AI workloads: compute, storage, managed AI services, and identity/access management.

Qualifications

• Strong analytical and problem-solving skills with a demonstrated ability to translate complex, ambiguous business requirements into practical, production-ready AI agent architectures.
• Excellent written and verbal communication skills; able to present and explain agentic AI concepts, architectures, and tradeoffs clearly to non-technical audiences including attorneys and firm leadership.
• Proven ability to manage multiple concurrent AI initiatives and priorities in a fast-paced, deadline-driven environment.
• Collaborative and team-oriented, with the ability to build effective working relationships across attorneys, business professionals, and technical staff.
• Knowledge of industry frameworks and emerging standards for AI governance, responsible AI use, and agentic system safety.
• Commitment to responsible AI practices, including transparency, explainability, bias awareness, and alignment with firm values and legal industry obligations.

Working Conditions

• Position is performed remotely with occasional travel to firm offices as needed; subject to time pressures, deadlines, and cross-functional dependencies.
• Occasional after-hours and weekend work may be required to support project delivery or time-sensitive production issues.

The above statements are intended to describe the general nature and level of work being performed by persons assigned to this job. They are not intended to be an exhaustive list of all duties, responsibilities, qualifications and skills required of personnel so classified. The firm reserves the right to revise or modify this job description at any time.