Staff Software Engineer / Architect - AI, CoCounsel FDE

Thomson Reuters develops trusted content and technology for professionals and organizations. The company is seeking a Staff Software Engineer / Architect - AI to lead the architecture and delivery of production-grade AI solutions for legal customers, while guiding system design, engineering practices, observability, and client technical discovery.

Responsibilities:

• Lead the end-to-end architecture, design, and delivery of AI-powered solutions for law firms and corporate legal departments, from concept through production deployment
• Review and guide system design, architecture, and code produced by AI Solution Engineers to ensure quality, scalability, security, and maintainability across engagements
• Build sophisticated legal AI solutions, including RAG pipelines, multi-agent workflows, event-driven services, and enterprise integrations tailored to legal use cases such as contract review, litigation support, discovery, and regulatory analysis
• Drive AI-native engineering practices across the team by embedding AI into development workflows, tooling, delivery processes, and technical standards
• Establish observability, evaluation, and trust frameworks for production AI systems, including monitoring, logging, tracing, model evaluation, and quality benchmarking
• Lead technical discovery with clients and legal stakeholders, translating legal workflows, business goals, and domain expertise into scalable technical architectures and solution plans
• Mentor engineers and partner with product, engineering, and legal experts to advance reusable solution patterns, accelerate delivery, and bring emerging AI capabilities into the team

Requirements:

• 7+ years of software engineering experience with deep expertise in system design, distributed systems, scalable architecture, and technical leadership
• Hands-on experience building and deploying AI/ML or LLM-powered applications in production, including strong knowledge of RAG architectures, orchestration frameworks, and evaluation practices
• Expert-level proficiency in Python and modern backend engineering, with experience designing RESTful APIs, async systems, and event-driven architectures
• Experience with cloud platforms such as AWS, Azure, or GCP, along with Infrastructure as Code and CI/CD practices for secure, scalable deployments
• Strong understanding of AI interoperability and agentic systems, including MCP, Agent-to-Agent workflows, third-party integrations, and tool-augmented architectures
• Experience with observability, monitoring, and AI quality tooling such as Datadog, Grafana, Prometheus, LangSmith, Langfuse, Braintrust, or similar platforms
• Excellent communication and stakeholder management skills, with the ability to engage credibly with engineers, legal professionals, and business leaders in ambiguous, high-impact environments