Senior Legal AI Platform Engineer

Seasoned experience in software, platform, integration, or infrastructure engineering, with independent ownership of complex production systems or components.

Hands-on ability with a general-purpose programming language such as Python, along with APIs, webhooks, structured data, automation, and systems troubleshooting.

Experience with cloud services, event-driven architectures, queues, containers, source control, CI/CD, automated testing, release controls, and production observability.

Practical experience with AI/LLM systems, including model APIs, retrieval or tool-use patterns, agents, evaluation, HITL controls, and the limits of generative output.

Strong identity and security fundamentals, including OAuth, service identities, least-privilege access, SSO/SCIM, secrets management, audit logging, and secure operational practices.

End-to-end technical ownership of CLM, CRM, workflow, service-desk, spend-management, repository, or adjacent operational platforms—from architecture through maintenance, not only configuration at the margins.

Strong systems thinking and data judgment, including the ability to translate legal, contractual, compliance, and policy requirements into workflows, fields, conditions, repositories, technical controls, and auditable evidence.

Good judgment in selecting the methods and techniques used to build solutions.

Demonstrated ability to investigate ambiguous problems, prioritize across multiple initiatives, and turn partially defined operational needs into shipped, maintainable outcomes with limited day-to-day direction.

Excellent communication and change-management skills across engineers, lawyers, analysts, security partners, finance stakeholders, People teams, and business-system owners.

The ability to advocate firmly for core convictions while remaining adaptable and keeping scope, ownership, and tradeoffs clear.

Experience with AI governance, privacy, information governance, or legal knowledge systems, particularly where the work requires balancing enablement with control.

Comfort working with reporting, metrics, dashboards, and BI-adjacent outputs that help Legal understand operational performance and communicate value.

A strong bias toward simple architecture, durable systems of record, measurable operation, clean documentation, and scalable operating patterns—not heroics, one-off fixes, or undocumented admin work.

Experience with AWS serverless services, containerized workloads, GitHub Actions, MCP or other tool-use integrations, and production AI evaluation is a strong plus.

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