Software Engineer - AI; Legal - CoCounsel Forward Deployed Engineering

Software Engineer - AI (Legal) (CoCounsel Forward Deployed Engineering)

Are you excited about building AI solutions that help legal professionals work faster, smarter, and with greater confidence? Do you enjoy operating at the intersection of engineering, legal workflows, and real‑world client problems? Join Thomson Reuters' CoCounsel Forward Deployed Engineering team – a high‑impact group focused on delivering practical legal AI solutions to law firms and corporate legal departments. With one million professionals relying on CoCounsel across 107 countries, the work you do here will have meaningful impact.

Over 20,000 law firms, corporate legal departments, top US courts, and Am Law 100 firms trust CoCounsel. The Forward Deployed Engineering team works directly on high‑value, real‑world legal AI problems – partnering closely with clients and internal teams to shape how AI is adopted in legal practice.

• Partner with AI Solution Engineers, Architects, and senior technical teammates to design, build, and deploy AI‑powered solutions for legal customers.
• Translate legal workflows and business needs into reliable technical solutions that combine foundation models, proprietary AI capabilities, and legal‑domain understanding.
• Engage in hands‑on engineering, client‑facing problem solving, and applied AI development.
• Contribute to technical discovery, solution delivery, prototyping, integrations, and evaluation of AI outputs for legal use cases.
• Ensure deployed systems are practical, accurate, secure, and aligned with high legal standards.
• Support client engagements through technical discovery sessions, requirement gathering, and scope definition.
• Work with stakeholders to understand workflows, pain points, and desired outcomes.
• Assist with demonstrations, proofs of concept, and early‑stage prototypes that inform design.
• Develop knowledge of legal terminology, processes, and operational constraints.
• Design, develop, and implement AI‑powered solutions for workflows such as contract review, litigation support, discovery automation, and regulatory analysis.
• Build and support retrieval‑augmented generation pipelines, agentic workflows, and other multi‑component AI systems.
• Configure and integrate solutions using CoCounsel, Westlaw, Practical Law, and other enterprise platforms.
• Develop automation scripts, APIs, and integration components tailored to customer environments.
• Collaborate with senior engineers and architects to ensure solutions are scalable, maintainable, and secure.
• Evaluate LLM outputs for legal accuracy, relevance, citation quality, consistency, and hallucination risk.
• Contribute to test cases, benchmarks, and evaluation workflows based on real legal tasks.
• Validate new capabilities against real‑world use cases.
• Support compliance with responsible AI principles, data privacy requirements, and enterprise security standards.
• Translate functional requirements into technical tasks and contribute to implementation planning.
• Document solutions, reusable components, and engineering best practices.
• Experiment with prompting strategies, workflow improvements, and emerging AI techniques.
• Stay current with developments in AI engineering, legal technology, and applied LLM systems.

• Background that includes JD, formal legal training, or significant experience in legal practice, operations, or technology.
• Familiarity with legal terminology and interest in legal workflows and AI.
• 2–4 years of software engineering experience, including production applications or integrations.
• Hands‑on Python experience and familiarity with modern AI/ML tooling and APIs.
• Understanding of core machine learning and LLM concepts, including prompt design, evaluation, and workflow orchestration.
• Experience integrating external APIs, automating workflows, or building data pipelines.
• Strong communication skills and ability to work with cross‑functional teams.
• Comfort in fast‑paced environments, quick learning, and multi‑project contributions.

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with containerization, deployment workflows, and modern development practices.
• Exper…