Staff Software Engineer, AI Product Engineering

Thomson Reuters

Staff engineer building AI-powered tax and accounting software at Thomson Reuters. Designing greenfield backend systems and AI-native products from architecture through production.

Posted 9/10/2026full-timeNew York City • Minnesota, Missouri, New York, Texas • 🇺🇸 United StatesLead💰 $127,400 - $236,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating large-scale backend systems, with a strong focus on Python, FastAPI, and AWS. Capable of leading cross-functional initiatives and mentoring engineers while designing scalable AI-native applications and architectures.

Highest-signal resume keywords

Python DevelopmentFastAPI FrameworkAWS Cloud PlatformAI-Native Application DevelopmentSystem Design and Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend DevelopmentAPI DesignData ModelingAsynchronous SystemsDistributed ArchitecturesRelational DatabasesGenerative AI ApplicationsTechnical LeadershipSoftware Lifecycle ManagementArchitecture Decision Making

Soft Skills

Strong CommunicationCross-Functional PartnershipProblem SolvingMentoring

Tools & Technologies

PostgreSQLDockerKubernetesCI/CDInfrastructure as CodeObservability

Industry Keywords

Greenfield Development0→1 Product LaunchAI SystemsFoundation ModelsReal-Time AI Workflows

Tech Stack

Tools & technologies

AWSCloudDjangoDockerFlaskKubernetesPostgresPythonTypeScript

About the role

Key responsibilities & impact

Own greenfield and 0→1 AI systems from technical discovery and architecture through implementation, production launch, monitoring, and iteration
Design and build production backend services using Python, FastAPI, PostgreSQL, and AWS
Build and evolve AI-native applications using large language models, AI agents, orchestration, retrieval, tool/function calling, and real-time AI workflows
Integrate models and services from OpenAI, Anthropic, and other foundation-model platforms
Design scalable APIs, data models, asynchronous workflows, and distributed services for high-volume AI applications
Influence architecture across reliability, scalability, latency, observability, security, testing, failure handling, and maintainability
Establish reusable engineering patterns and technical standards across teams and workstreams
Evaluate AI behavior in production and build quality measurement, experimentation, evaluation, guardrails, and continuous improvement mechanisms
Partner with Product and Design to translate customer problems into scalable technical solutions
Provide hands-on technical leadership across complex cross-functional initiatives
Participate in design, implementation, debugging, and code review
Mentor engineers and guide architectural and engineering trade-offs
Identify technical risks and drive solutions across systems and teams

Requirements

What you’ll need

Significant software engineering experience building and operating large-scale, production-grade backend systems
Strong, recent hands-on development experience with Python
Production experience with backend frameworks such as FastAPI, Flask, or Django; FastAPI strongly preferred
Experience designing APIs, backend services, data models, asynchronous systems, and distributed architectures
Experience with relational databases such as PostgreSQL and a major cloud platform; AWS strongly preferred
Experience personally designing, building, and launching greenfield or 0→1 products and systems
Experience making architecture decisions affecting multiple systems, teams, or major product capabilities
Strong system-design skills covering scalability, reliability, performance, failure modes, and operational trade-offs
Experience across the full software lifecycle, including architecture, implementation, deployment, observability, debugging, incident response, and production iteration
Ability to influence technical direction without formal authority
Strong communication and cross-functional partnership skills
Ability to operate effectively in ambiguous, fast-moving environments
Hands-on production experience building generative AI or AI-native applications strongly preferred
Experience with LLM-powered agents, agent orchestration, tool/function calling, RAG, embeddings, vector search, retrieval systems, or real-time AI interactions preferred
Experience integrating commercial or open foundation models, including OpenAI or Anthropic, preferred
Experience building customer-facing SaaS or product software in a startup, scale-up, or similarly high-ownership environment preferred
Experience with Docker, Kubernetes, CI/CD, infrastructure as code, observability, and modern cloud-native engineering preferred
Exposure to TypeScript or modern frontend frameworks helpful but not required

Benefits

Comp & perks

Flexible hybrid working environment
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
Mental, physical, and financial wellbeing resources
Two paid volunteer days off annually
Health, dental, vision, disability, and life insurance programs
Competitive 401(k) plan with company match
Sick and safe paid time off
Paid holidays, including two company mental health days off
Parental leave
Sabbatical leave
Optional hospital, accident and sickness insurance
Optional life and AD&D insurance
Flexible Spending and Health Savings Accounts
Fitness reimbursement
Employee Assistance Program
Group Legal Identity Theft Protection benefit
529 Plan access
Commuter benefits
Adoption & Surrogacy Assistance
Employee Stock Purchase Plan
Annual Bonus based on enterprise and individual performance