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Senior Manager, AI Engineering
Thomson Reuters. Build, hire, mentor, and develop a high-performing team of backend, platform, and AI engineers .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in leading and mentoring high-performing engineering teams, particularly in backend and AI development. Proficient in setting technical direction and modernizing systems to enhance scalability and reliability in legal technology.
Highest-signal resume keywords
10+ Years ExperienceHands-On Proficiency In PythonStrong Cloud Experience With AWSExperience Leading Multi-Team InitiativesExperience With Machine Learning Systems
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringBackend DevelopmentMachine LearningGenerative AIData ProcessingDistributed SystemsAI EvaluationPrototypingModernizationTesting Standards
Soft Skills
MentoringCollaborationProblem-SolvingAdaptabilityRelationship Building
Tools & Technologies
AWSAzureGCPPythonJava
Industry Keywords
Legal TechnologyLegal ResearchHigh-Accuracy Data DomainsAI TransformationMatrixed Organization
Tech Stack
Tools & technologiesAWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaPython
About the role
Key responsibilities & impact- Build, hire, mentor, and develop a high-performing team of backend, platform, and AI engineers
- Set technical direction and create a scalable technical strategy and roadmap for KeyCite
- Partner with Product, Editorial, Research, Engineering, and AI teams
- Lead development and productionization of generative AI and machine learning capabilities for legal research
- Modernize KeyCite processing, publishing, and services to improve scalability, reliability, and delivery speed
- Work with AI researchers and legal domain experts to apply AI, machine learning, and traditional software to trusted professional workflows
- Establish standards for architecture, reliability, observability, experimentation, testing, and AI evaluation
- Lead initiatives from prototype through productionization, measurement, and continuous improvement
- Remove blockers and build strong cross-functional relationships
Requirements
What you’ll need- 10+ years experience
- At least 7 years of software engineering experience
- Experience that began before the wide adoption of generative AI
- At least 2 years of people-management experience
- Experience managing teams of 10 or more people
- Experience leading multi-team initiatives
- Hands-on proficiency in Python and Java
- Experience building scalable backend or distributed systems
- Strong cloud experience, with AWS preferred; strong Azure or GCP experience also considered
- Experience taking machine learning or generative AI systems from prototype into production
- Experience leading teams through modernization of existing systems while keeping them reliable
- Ability to work with ambiguity and drive change in a fast-moving environment
- Preferred: experience with LLM evaluation, retrieval, grounding, or agent-based architectures
- Preferred: experience in legal technology, legal research, or regulated/high-accuracy professional-data domains
- Preferred: experience at a company navigating an AI transformation
- Preferred: large-scale data processing, search, knowledge graph, or data platform experience
- Preferred: experience leading or working alongside engineering managers in a matrixed organization
Benefits
Comp & perks- Flexible hybrid working environment
- Work from anywhere for up to 8 weeks per year
- Continuous learning and skill development
- Grow My Way programming
- Flexible vacation
- Two company-wide Mental Health Days off
- Access to the Headspace app
- Retirement savings
- Tuition reimbursement
- Employee incentive programs
- Resources for mental, physical, and financial wellbeing
- Two paid volunteer days off annually
- Opportunities to get involved with pro-bono consulting projects and ESG initiatives
- Annual Bonus based on a combination of enterprise and individual performance
- Flexible and supportive benefits and other wellbeing programs