Senior AI Engineer: Agent Platforms & Scale

Thomson Reuters Foundation; Eagan (MN); Hybrid; USD 110,000 - 204,000; Full time

Benefits offered by this job

Hybrid Work Model

Career Development

Mental Health Days

Job summary

Thomson Reuters Foundation in the United States seeks a Senior AI Engineer to own end-to-end AI agent systems, built on LLM APIs, agent SDKs, and cloud-backed runtimes. You will architect multi-component workflows, mentor engineers, and contribute to observability, evaluation pipelines, and safe release practices to scale AI agents in production.

This role supports a hybrid-work model with flexible development cycles, strong benefits, and opportunities to shape how legal AI tools empower

Qualifications

• Experience architecting and shipping production software with AI/LLM-powered products or agent systems.
• Experience with modern LLM APIs, agent frameworks/SDKs, or agent-to-tool integration.
• Experience owning complex technical projects end-to-end, from design through production delivery.

Responsibilities

• Architect and deliver complex AI agent systems end-to-end.
• Build production AI agent systems on LLM APIs, agent SDKs, and orchestration/runtime infrastructure.
• Contribute to agent observability and evaluation practices (tracing, evals, drift detection).
• Adopt progressive delivery practices with feature flag rollout and quality signals.
• Participate in RFCs/ADRs and cross-cutting design reviews.
• Mentor engineers on AI-native, agentic development practices.
• Collaborate with product and engineering to translate requirements into solid designs.

Skills

AI/LLM systems

Agent frameworks/SDKs

Backend engineering

Observability

Mentoring

Cloud infrastructure

Production reliability

Tools

LLM APIs

Agent SDKs

Agent runtime infra

Job description

Thomson Reuters Foundation in the United States seeks a Senior AI Engineer to own end-to-end AI agent systems, built on LLM APIs, agent SDKs, and cloud-backed runtimes. You will architect multi-component workflows, mentor engineers, and contribute to observability, evaluation pipelines, and safe release practices to scale AI agents in production.

This role supports a hybrid-work model with flexible development cycles, strong benefits, and opportunities to shape how legal AI tools empower