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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer / Architect - AI - Legal FDE - **Company:** Thomson Reuters Holdings Inc. - **Location:** Frisco, TX, United States - **Salary:** $183,100 - $340,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, AI Evaluation, A/B Testing, Adobe InDesign, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Continuous Integration, Cursor, Document Management Systems, Distributed Systems, Python (Programming Language), Westlaw, OAuth, Open Source Technology, Openid Connect, Prometheus, JSON Web Token, Software Engineering, Datadog, Cloud Platform System, GitHub Copilot, LangChain, Retrieval-Augmented Generation, Large Language Models, Claude Code, Grafana, Multi-Agent Systems, Langfuse — LLM Observability and Analytics Platform, Fastapi, Event Driven Architecture, LangSmith, Kubernetes, Infrastructure Automation Frameworks, AutoGen, Free and Open-Source Software, PydanticAI Framework, Machine Learning Operations, Evaluation of Large Language Models, Restful APIs, Model Context Protocol, Terraform, Docker, Agent2Agent Protocol - **Published:** November 10, 2026 - **Apply:** https://thomsonreuters.wd5.myworkdayjobs.com/External_Career_Site/job/United-States-of-America-Frisco-Texas/Job-Posting-Title-Principal-Software-Engineer---Architect---AI---Legal-FDE_JREQ205196 ## About the Role * 12+ years of software engineering experience, with deep expertise in system design, distributed systems, and architecture, and a track record of leading highly complex, high-risk projects. * Extensive experience owning technical requirements and strategy, setting technology roadmaps, and prioritizing between competing features and investments. * Expert-level, hands-on experience building and deploying AI/ML and LLM-powered applications in production. * Deep proficiency with orchestration frameworks such as LangChain, LangGraph, PydanticAI, or AutoGen, and expert understanding of RAG architectures and vector databases. * Hands-on experience with Model Context Protocol (MCP) and Agent-to-Agent (A2A) patterns for interoperable, tool-augmented AI systems. * Expert Python (FastAPI or equivalent), with strong experience in RESTful, async, and event-driven architectures. * Experience with a major cloud platform (AWS, Azure, or GCP) and Infrastructure as Code (Terraform, CDK, or equivalent). * Production observability experience (Datadog, Grafana, Prometheus, or similar) and experience with AI evaluation platforms (LangSmith, Langfuse, Braintrust, or W&B). * Strong background in secure API development using OAuth 2.0, OpenID Connect, and JWT. * Demonstrated fluency with AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) and a track record of driving AI-native engineering practices. * Proven ability to influence across teams and domains, advise senior leadership, and communicate complex ideas at multiple levels of an organization. * Autonomy, sound judgment, comfort with ambiguity in a fast-paced agile environment, and strong attention to detail. * Recognized as a technical role model and leader in your field., * Experience in a regulated industry (legal, fintech, or healthcare), with familiarity with compliance and data privacy requirements. * Experience building agentic AI systems with autonomous decision-making. * Familiarity with legal platforms, document management systems, and legal technology ecosystems. * Container orchestration (Docker/Kubernetes) and MLOps/LLMOps lifecycle management. * Understanding of transformer model scaling, limitations, and fine-tuning. * External presence through conference talks, publications, patents, open-source contributions, or standards participation. * Experience developing vision documents and leading cross-business-unit technology strategy., * Hybrid Work Model: We've adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected. ## Description Technical Vision and Strategy * Define and drive the long-term technical vision and strategy for FDE, including vision documents, technology requirements, and roadmaps tied to product and business objectives. * Lead the selection, evaluation, and adoption of technologies, frameworks, and patterns, and build consensus across teams. * Identify where emerging capabilities such as agentic systems, MCP and A2A interoperability, and new model and orchestration patterns could cause a transformational shift, and communicate the opportunities and trade-offs to senior leadership. * Contribute to cross-functional and cross-business-unit engineering strategy, standards, and, where appropriate, patents. Architecture and Delivery of Complex AI Systems * Lead complex, high-risk, high-visibility AI initiatives from concept through production, staying hands-on in design, prototyping, and code for the hardest problems. * Architect scalable, secure AI systems that integrate with client environments, including document management systems, enterprise platforms, and legal technology ecosystems. * Design RAG pipelines, multi-agent orchestration, event-driven backends, and agentic workflows using CoCounsel, Westlaw, and Practical Law capabilities, plus third-party AI APIs. * Build reusable AI components, frameworks, and solution templates that scale delivery across the team. * Set standards for MLOps/LLMOps, Infrastructure as Code, and CI/CD so delivery is secure, repeatable, and fast. * Identify weaknesses in existing designs and drive remedies. Quality, Observability, and Trust * Set the strategy for AI monitoring and observability, covering performance, output quality, latency, cost, and production reliability risk. * Own LLM evaluation, including accuracy, hallucination risk, citation quality, A/B testing, and red-teaming, and define quality benchmarks grounded in real legal workflows. * Ensure every solution meets ethical AI, data protection, and enterprise security requirements. * Drive operational excellence across the software development lifecycle, including post-launch measurement. Client and Stakeholder Engagement * Act as the senior technical voice in discovery on high-value engagements, scoping use cases, shaping architectures, and building credibility with legal and technical executives. * Present complex technical concepts and strategy to audiences from engineers to business unit executives, and negotiate solutions between key stakeholders. * Work with legal SMEs to translate professional reasoning and domain heuristics into pipeline design, evaluation criteria, and benchmarks. * Anticipate customer and market needs and feed field insights back into the product roadmap. Leadership, Mentorship, and Culture * Mentor and coach Staff, Senior, and Lead engineers, and indirectly lead a small team of engineers and technical experts on ambiguous problems. * Review architecture and design at team and sub-unit levels and give authoritative feedback. * Strengthen engineering culture through knowledge sharing and by championing AI-native tools and practices. * Work with program and project managers to bring the technical dimension into status and risk reporting, and consult on budgets for large programs where applicable. * Represent Thomson Reuters externally through speaking, publications, community engagement, or open-source and standards participation.