Thomson Reuters is hiring a Staff Software Engineer / Architect - AI to lead the architecture and delivery of AI solutions for law firms and corporate legal departments. The role involves guiding system design, building AI solutions, and mentoring engineers to advance AI-native engineering practices.
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