AI Engineer

We are building custom AI systems that enhance how legal knowledge is structured, surfaced, and applied across the firm. Our team develops production-ready AI solutions and works closely with attorneys and partners to support high-impact legal workflows.

We are seeking an AI Engineer with experience building AI-driven applications, including RAG pipelines and LLM-powered systems. This role focuses on implementing and improving well-defined features within existing AI systems, contributing to design, experimentation, and production deployment.

This role sits within Practice Innovation and collaborates closely with Legal Engineering, Practice Solutions, Knowledge Management, Cloud/Infrastructure teams, and other stakeholders across the firm.

Duties & Responsibilities

• Design, build, and enhance retrieval-based AI systems, data pipelines, and workflow-driven applications.
• Develop and optimize AI agents that orchestrate multi-step legal workflows and tool integrations.
• Apply modern RAG (Retrieval-Augmented Generation) design patterns to improve system accuracy, reliability, and performance.
• Conduct structured experimentation and evaluation to refine prompts, retrieval strategies, agent behavior, and model outputs.
• Contribute to data ingestion, cleaning, structuring, and indexing processes supporting AI applications.
• Support deployment, monitoring, and continuous improvement of AI tools in production environments.
• Take ownership of well-defined features and contribute to system enhancements from design through production.
• Partner with Cloud, Networking, and Infrastructure teams to ensure secure, scalable, and reliable deployments.

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 2+ years of professional experience in software engineering, machine learning, or AI-related roles.

• Hands-on experience building LLM-based applicationsin production or near-production environments.
• Experience with vector databases and similarity search (e.g., Qdrant, Pinecone, Weaviate, or similar).
• Solid understanding of RAG architectures and retrieval optimization.
• Experience working with structured and unstructured data.
• Strong proficiency in Python and software engineering fundamentals (clean code, testing, system design).
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Strong analytical and problem-solving skills.
• Ability to operate independently on well-scoped problems and escalate appropriately when needed.
• Strong communication skills with the ability to work effectively across technical and non-technical audiences.

• Experience deploying AI agents or LLM-powered systems in production environments.
• Experience with Azure cloud services (strong plus).
• Familiarity with monitoring, logging, and evaluation practices for production AI systems.
• Experience working in enterprise or regulated environments.