Senior Software Engineer - AI, CoCounsel FDE

Thomson Reuters•Frisco, TX

1d•Hybrid

About The Position

The Senior Software Engineer – AI joins Thomson Reuters’ CoCounsel Forward Deployed Engineering team to design, build, and deploy bespoke AI solutions for law firms and corporate legal departments. Working with the AI Solutions Architect, Senior Legal AI Engineers, and other AI engineers, the role takes architectural direction and solution designs through implementation and into production, while contributing to solution design and owning the quality of delivered systems. This is a client-facing engineering role involving technical discovery, use-case scoping, prototyping, and collaboration with legal subject-matter experts. The engineer builds tailored AI systems for legal workflows, such as contract review, litigation support, discovery automation, and regulatory analysis, and ensures those systems meet legal professionals’ high standards for trust, security, and quality. The role also contributes to evaluation practices, reusable solution templates, and exploration of emerging AI techniques and interoperability standards.

Requirements

At least 5 years of software engineering experience, with a strong foundation in system design, distributed systems, and clean architecture.
At least 2 years of hands-on experience building and deploying AI/ML solutions in production, including LLM-powered applications.
Proficiency with orchestration frameworks such as LangChain, LangGraph, PydanticAI, or AutoGen, and a solid understanding of RAG architectures and vector databases.
Experience with MCP and A2A workflow patterns for interoperable, tool-augmented AI systems.
Strong proficiency in Python, including FastAPI or an equivalent framework, and experience building RESTful and asynchronous, event-driven architectures.
Experience with AWS, Azure, or GCP and familiarity with Infrastructure as Code tools such as Terraform or CDK.
Experience with observability and monitoring stacks such as Datadog, Grafana, or Prometheus for production AI systems.
Experience with AI evaluation platforms such as LangSmith, Langfuse, Braintrust, or Weights & Biases, and ability to contribute to structured evaluation pipelines for LLM applications.
Strong background in secure API development, including authentication and authorization protocols such as OAuth 2.0, OpenID Connect, and JWT.
Strong prompt-engineering skills, including the ability to design, iterate, and optimize prompts for specialized domain tasks.
Demonstrated fluency with AI-assisted development tools such as Claude Code, Cursor, or GitHub Copilot.
Excellent communication skills and ability to engage credibly with engineers, non-technical stakeholders, and legal professionals.
Ability to work independently, navigate ambiguity, and contribute in client-facing workshops and discovery sessions.

Nice To Haves

Fluency in legal terminology and demonstrated experience working directly within or alongside legal teams.
Experience in a regulated industry such as legal, fintech, or healthcare, and familiarity with related compliance and data privacy requirements.
Experience with legal platforms, document management systems, and legal technology ecosystems.
Experience with container orchestration, including Docker or Kubernetes.
Knowledge of MLOps and LLMOps practices for production AI system lifecycle management.
Understanding of the scaling, limitations, and fine-tuning of transformer-based models.
Familiarity with emerging AI interoperability standards and protocols, including MCP ecosystem tooling and A2A communication patterns.
A portfolio demonstrating skill in building complex, production-grade AI solutions.

Responsibilities

Design and implement AI-powered solutions tailored to law firm and corporate legal workflows, including contract review, litigation support, discovery automation, and regulatory analysis.
Build scalable, secure, and maintainable AI systems within architectural frameworks set by the AI Solutions Architect.
Architect retrieval-augmented generation (RAG) pipelines, custom AI agents, and multi-component systems that integrate securely with client environments, document management systems, and enterprise platforms.
Build and configure multi-step agentic workflows using CoCounsel, Westlaw, Practical Law, third-party AI APIs, and enterprise integrations.
Implement Agent-to-Agent (A2A) workflows and Model Context Protocol (MCP) integrations for interoperability with AI agents, external tools, data sources, and enterprise systems.
Design and deploy customer-specific automation pipelines and integration scripts.
Implement MLOps and LLMOps practices for scalable, maintainable production deployments.
Implement monitoring, logging, and tracing to track LLM performance, latency, token usage, and production system health.
Use AI evaluation platforms to assess model outputs, track evaluation metrics, and identify quality regressions.
Contribute to LLM evaluations for accuracy, citation quality, hallucination risk, and suitability for high-stakes legal use.
Develop and maintain evaluation benchmarks, test suites, and red-teaming protocols grounded in legal workflows; communicate findings to inform product and engineering roadmaps.
Ensure solutions comply with ethical AI principles, data protection standards, and enterprise security requirements.
Participate in client technical discovery, contributing to use-case scoping, solution design discussions, and early-stage prototyping.
Translate legal workflows, pain points, and client goals into engineering tasks and implementation plans.
Conduct technical demonstrations and prototypes to support solution design and client confidence.
Build trust with legal professionals through fluency in legal terminology, workflows, and practical constraints.
Work with legal subject-matter experts to translate professional reasoning and judgment into AI pipeline design, evaluation criteria, and benchmarks.
Collaborate with Senior Legal AI Engineers, the AI Solutions Architect, and fellow AI engineers to deliver solutions across engagements.
Contribute to team knowledge-sharing, internal documentation, and reusable solution templates.
Evaluate and prototype emerging AI techniques, agentic frameworks, MCP-based integrations, and prompt-engineering approaches.
Stay current with AI research and the legal AI landscape, and bring new ideas to the team.

Benefits

Comprehensive health, dental, vision, disability, and life insurance programs.
401(k) plan with company match.
Flexible vacation, sick and safe paid time off, and paid holidays, including two company mental health days.
Parental leave and sabbatical leave.
Flexible work arrangements, including work-from-anywhere for up to eight weeks per year.
Access to the Headspace app and Employee Assistance Program.
Tuition reimbursement.
Employee incentive programs and an annual bonus may be available based on enterprise and individual performance.
Fitness reimbursement.
Flexible Spending and Health Savings Accounts.
Commuter benefits.
Adoption and surrogacy assistance.
Employee Stock Purchase Plan.
Two paid volunteer days annually and opportunities for pro-bono consulting and ESG initiatives.
Career development and continuous learning programs.
Optional hospital, accident and sickness insurance; optional life and AD&D insurance; group legal identity theft protection; and access to a 529 Plan.