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Senior Software Engineer – AI
Thomson Reuters. Architect and deliver complex AI agent systems end-to-end, including multi-component pipelines, tool integrations, and multi-step reasoning .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and delivering AI agent systems, with a strong focus on production reliability, observability, and integration with existing platforms. Proven ability to mentor engineers and contribute to a collaborative technical culture while managing complex projects end-to-end.
Highest-signal resume keywords
AI Agent System ArchitectureModern LLM API IntegrationProduction Reliability PracticesMentorship and Technical LeadershipDistributed Systems Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI/LLM-Powered Product DevelopmentAgent Frameworks/SDKsService ArchitectureCloud InfrastructureMonitoring and Evaluation PipelinesIncident ResponseQuality Regression DetectionFeature FlaggingPhased RolloutBlue/Green Deployment
Soft Skills
CollaborationTechnical Culture ContributionHigh Autonomy
Tools & Technologies
AWS Bedrock AgentCoreIntegration EcosystemsPlugin/Extension Systems
Industry Keywords
Legal Domain ExpertiseRegulated DomainsProfessional ServicesFiduciary Domains
Tech Stack
Tools & technologiesAWSCloudDistributed Systems
About the role
Key responsibilities & impact- Architect and deliver complex AI agent systems end-to-end, including multi-component pipelines, tool integrations, and multi-step reasoning
- Build production AI agent systems using modern LLM APIs, agent SDKs, and orchestration/runtime infrastructure
- Integrate AI agent systems with existing platform services
- Contribute to agent observability and evaluation practices, including tracing, automated evaluations, and quality/drift detection
- Adopt and extend progressive delivery practices such as feature-flagged rollout and earlier-stage quality signals
- Participate in cross-cutting design reviews and technical decisions through RFCs/ADRs
- Mentor engineers and model AI-native, agentic development practices
- Collaborate with product and engineering peers to translate requirements into technical designs
- Own meaningful systems end-to-end and build infrastructure, tooling, and observability for reliable AI agents at scale
Requirements
What you’ll need- Strong experience architecting and shipping production software systems
- Hands-on experience building AI/LLM-powered products or agentic systems, not solely classical ML/data science
- Direct experience with modern LLM APIs, agent frameworks/SDKs, or agent-to-tool integration protocols
- Experience owning complex technical projects end-to-end, from design through production delivery
- Strong backend engineering fundamentals, including distributed systems design, service architecture, and cloud infrastructure
- Experience with production reliability and observability practices, including monitoring, evaluation pipelines, incident response, and quality regression detection
- Ability to mentor other engineers and contribute to a strong technical culture
- Comfort working with high autonomy on a fast-moving, senior-heavy team using AI-native/agentic engineering practices
- Experience with developer-facing platforms, plugin/extension systems, or integration ecosystems (preferred)
- Familiarity with progressive delivery practices such as feature flagging, phased rollout, and blue/green deployment at scale (preferred)
- Experience with managed agent runtime infrastructure such as AWS Bedrock AgentCore or similar (preferred)
- Domain expertise in legal, regulated, professional-services, or fiduciary domains is a plus, but not required
Benefits
Comp & perks- Flexible hybrid working environment for office-based roles
- Work from anywhere for up to 8 weeks per year
- Flexible vacation
- Two company-wide Mental Health Days off
- Headspace app access
- Retirement savings
- Tuition reimbursement
- Employee incentive programs
- Resources for mental, physical, and financial wellbeing
- Two paid volunteer days off annually
- Pro-bono consulting and ESG initiative opportunities
- United States: health, dental, vision, disability, and life insurance
- United States: competitive 401(k) plan with company match
- United States: sick and safe paid time off
- United States: paid holidays
- United States: parental leave
- United States: sabbatical leave
- United States: optional hospital, accident and sickness insurance
- United States: optional life and AD&D insurance
- United States: Flexible Spending and Health Savings Accounts
- United States: fitness reimbursement
- United States: Employee Assistance Program
- United States: Group Legal Identity Theft Protection benefit
- United States: 529 Plan access
- United States: commuter benefits
- United States: Adoption & Surrogacy Assistance
- United States: Employee Stock Purchase Plan
- Annual Bonus eligibility based on enterprise and individual performance