The AI Engineer is responsible for developing the custom AI capabilities that extend value across Manatt beyond what commercial tools provide out of the box. Where the AI Solutions Analysts administer and deploy the firm's existing AI platforms, the AI Engineer builds what does not yet exist — designing integrations, APIs, and purpose-built AI applications that bring AI-driven productivity to attorneys and professionals throughout the firm. 

This individual works at the intersection of software engineering and applied AI, translating complex legal and operational requirements into scalable, production-grade solutions. The AI Engineer works closely with the AI & Solutions Architect on design standards and with the AI Solutions Analysts on use case identification, ensuring that custom-built capabilities can be handed off for ongoing administration and broad deployment.

Key Responsibilities:

Custom AI Development

• Design and develop custom AI applications, integrations, and workflow automations that address high-priority use cases identified by the AI Solutions Analysts, AI & Solutions Architect, and other firm leadership needs.
• Build and maintain integrations between the firm's AI platforms, data systems, and business applications using APIs, SDKs, and custom middleware — ensuring reliability, security, and maintainability.
• Develop retrieval-augmented generation (RAG) pipelines that connect firm knowledge — matters, precedents, templates, policies — to AI models in a governed and permissioned manner.
• Build AI agents and multi-step automated workflows designed for handoff to the AI Solutions Analysts for ongoing administration and firmwide deployment.

Architecture Alignment & Engineering Standards

• Collaborate with the AI & Solutions Architect to ensure all custom development adheres to firm architectural standards, security requirements, coding practices, and deployment pipelines.
• Maintain production code, manage version control, and ensure all deployed AI solutions are monitored, documented, and supportable by the broader AI team.
• Evaluate and prototype emerging AI frameworks and tools, providing structured recommendations to the Architect and Program Lead on applicability to the firm's use case roadmap.
• Contribute to the definition and continuous improvement of engineering standards, testing practices, and deployment processes for AI systems at the firm.

Use Case Delivery & Stakeholder Collaboration

• Work cross-functionally with IT, Legal Operations, and Consulting stakeholders to gather requirements, validate solutions, and ensure that built capabilities solve real workflow problems at scale.
• Translate complex technical capabilities into accessible workflow solutions that can be leveraged by attorneys and professionals who are not AI power users.
• Partner with AI Solutions Analysts to identify workflow gaps that exceed the configuration capabilities of existing tools and warrant custom engineering effort.
• Participate in the documentation of use cases, solution patterns, and technical specifications, contributing to the firm's growing AI knowledge base.

Innovation & Continuous Improvement

• Stay current on developments in LLM capabilities, AI agent frameworks, and enterprise AI engineering, translating relevant advances into actionable prototypes and proposals.
• Identify and recommend opportunities to productize successful one-off AI solutions into reusable components that can be deployed across multiple practice groups.
• Participate in vendor evaluations, contributing hands-on technical assessments of AI tools under consideration by the firm.

Required Skills & Expertise:

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• 4–7 years of software engineering experience, with at least 2 years focused on AI/ML or LLM application development in a production environment.
• Strong proficiency in Python; hands-on experience with AI/ML libraries and frameworks including LangChain, LlamaIndex, OpenAI SDK, Anthropic SDK, or equivalent.
• Demonstrated experience building production RAG systems, AI agents, or LLM-powered applications that have been deployed to and used by real end users.
• Solid understanding of REST APIs, cloud services (Microsoft Azure preferred), and enterprise integration and security patterns.
• Familiarity with vector databases and embedding infrastructure (Pinecone, Weaviate, Azure AI Search, or equivalent).
• Experience working in security-conscious environments with an understanding of data access controls, secrets management, and compliance requirements.
• Ability to work autonomously on ambiguous problems and communicate technical progress and tradeoffs clearly to non-technical stakeholders.
• Experience in a legal, financial services, or professional services technology environment preferred.
• Familiarity with legal-industry systems (preferred): iManage, document management platforms, and law firm line-of-business applications.

The base annual pay range for this role is between $145,000–$175,000. The base pay to be offered will vary and depend on skills and qualifications, experience and location. A full range of medical, financial and/or other benefits dependent on the position will also be offered.