AI Engineer

Overview

In this role you will help build a new R&D AI capability for legal services, delivering end-to-end AI products. You’ll work in a small, multidisciplinary team to turn product designs into secure, observable software with practical deployment. Expect hands-on development across UI, backend, AI orchestration, and enterprise integrations, guided by enterprise security and deployment patterns. The work focuses on making AI workflows useful, observable, and scalable for lawyers and business users, with measurable improvements in quality and cost. This is a hands-on, production-focused opportunity to shape AI-enabled legal tech at scale.

Responsibilities

• Develop AI-enabled product features across UI, backend, AI orchestration, retrieval, and enterprise integrations.
• Design agentic AI workflows with structured outputs, tool calls, and human-review steps.
• Create reusable agent harnesses with state, context, traces, and test fixtures for consistency and safety.
• Implement grounded retrieval and context patterns using approved data products and sources with evidence and citations.
• Design and operate evaluation harnesses, including test sets, scenarios, grading, and feedback loops.
• Manage prompts, model configurations, tool schemas, routing, fallbacks, and latency/cost trade-offs.
• Implement AI observability through traces, logs, metrics, and evaluation results for continuous improvement.
• Build APIs and interfaces to expose AI outputs and enable approvals and user feedback.
• Write maintainable Python and TypeScript, using Docker, Git, automated testing, and CI/CD.
• Apply security, authentication, data handling, deployment and release patterns in collaboration with firm tech teams.

Key requirements

• ≥3 years producing production AI products, with SaaS experience; legal tech experience is advantageous but not required.
• Strong Python, plus practical TypeScript or JavaScript; experience with FastAPI or Flask and frontend frameworks (React/Next.js).
• Experience with LLM APIs, structured outputs, retrieval/embeddings, tool calling and workflow orchestration.
• Experience building agentic systems with state/context management, tools, and human-review controls.
• Experience evaluating AI workflows, test design, prompt experiments, and user feedback integration.
• Proven ability to move AI features from prototype to production with testing, monitoring, and improvement.
• Experience with AI observability, tracing and evaluation tooling; grounded retrieval and evidence/citations understanding.
• API design and enterprise integration experience; secure handling of authentication, authorization, secrets and sensitive data.
• Comfort with Docker, Git, automated testing and CI/CD; able to ship maintainable, repeatable work.
• Strong debugging and systems-thinking skills; ability to explain AI behavior and trade-offs to technical and non-technical stakeholders.

• collaborative
• clear communicator
• problem-solving
• Python
• TypeScript/JavaScript
• FastAPI/Flask

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