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About This Role
Job Description
Thomson Reuters products power the professionals shaping the world. Confirmation is the industry-leading audit confirmation platform, connecting audit firms, their clients, and thousands of responding institutions to securely verify balances and transactions with speed and certainty.
As a Staff Software Engineer – AI on the Confirmation Product Engineering team, you will be a hands-on technical leader building and delivering production platform and AI capabilities . This role requires strong production C#/.NET engineering experience , along with Python experience for AI/ML development and integration .
We are looking for an engineer who has personally built and delivered AI features into production as part of enterprise software products. This is not a pure architecture, research, data science, or proof-of-concept role. You will remain deeply hands-on in the code while providing Staff-level technical leadership.
You will design and build C#/.NET backend and distributed systems and use Python to develop and integrate AI/ML capabilities , including large language model (LLM)-powered applications, AI agents, orchestration, retrieval, and document understanding. You will partner with Principal Engineers and cross-functional teams to establish AI engineering patterns, develop Model Context Protocol (MCP) servers and agent-based capabilities, and build reliable and scalable AI infrastructure.
Key Responsibilities
- Architect, develop, and deliver production backend and platform services using C#/.NET , PostgreSQL, AWS, microservices, and distributed-system patterns.
- Build production AI/ML capabilities using Python , including LLM integration, AI agents, orchestration, retrieval, and multi-step AI workflows.
- Lead hands-on AI engineering initiatives across product and infrastructure, including agent-based workflows, retrieval systems, and AI-assisted document processing.
- Build and evolve AI orchestration capabilities, including routing, tool calling, MCP servers, multi-step workflows, safety controls, guardrails, evaluation, and resilient error handling around third-party LLMs.
- Design reliable, scalable, high-throughput distributed systems and AI workloads , incorporating caching, queuing, rate limiting, model failover, observability, resilience, and cost/performance optimization.
- Develop retrieval and data capabilities using document search, vector stores, embeddings, semantic search, and indexing strategies for large-scale audit and confirmation use cases.
- Provide hands-on Staff-level technical leadership by setting technical direction, influencing engineering standards, mentoring engineers, and continuing to personally design, code, build, and deliver production systems.
Required Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, a related field, or equivalent professional experience.
- 7+ years of progressive software engineering experience , including hands-on development, architecture, and delivery of large-scale production systems.
- Strong, recent, hands-on C#/.NET production development experience , including building backend services and APIs using C#/.NET and ASP.NET Core or similar technologies.
- Hands-on Python experience for AI/ML system development , including model integration, AI orchestration, APIs, data pipelines, or comparable production use cases.
- Demonstrated experience personally building and delivering AI/ML features into production , including LLM-powered applications, AI agents, retrieval/RAG, orchestration, or comparable AI-native capabilities.
- Strong hands-on platform and distributed-systems engineering experience , including microservices, system integration, data modeling, REST or GraphQL APIs, relational databases, observability, resilience, scalability, and performance optimization.
- Experience implementing appropriate AI safety controls, guardrails, evaluation, reliability, and production operational practices .
- Proven experience leading complex engineering initiatives from architecture and hands-on implementation through deployment, rollout, and long-term production operation.
- Proven ability to operate as a hands-on Staff-level technical leader , providing technical direction and mentoring engineers while continuing to actively design, code, build, and deliver production software.
- Strong communication and cross-functional collaboration skills with the ability to partner effectively with engineering, product, design, user experience, research, and machine learning teams.
Candidates must have hands-on production AI delivery experience. AI experience limited to personal projects, side projects, coursework, experimentation, or proof-of-concept work alone does not meet this requirement.
Preferred Qualifications
- Hands-on experience integrating LLM APIs such as OpenAI or Anthropic into production applications, including prompt and response management, cost controls, reliability, and safety considerations.
- Experience with vector databases, embeddings, semantic search, and custom retrieval pipelines .
- Experience designing automated testing, AI evaluation, reliability, and release practices for systems with non-deterministic model behavior.
- Familiarity with actor-model architectures and frameworks , such as Microsoft Orleans or Akka, for resilient, message-driven distributed systems.
- Experience with AWS , containerized microservices using Docker and Kubernetes, and CI/CD pipelines such as GitHub Actions or similar technologies.
- Experience with modern JavaScript frameworks, particularly Angular and TypeScript .
- Experience working in industries where correctness, auditability, security, and regulatory compliance are important, such as financial technology, audit, tax, or legal technology.
Experience interacting directly with customers and translating customer or business needs into scalable technical solutions. *
#LI-TH1
This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization.
What’s in it For You?
- Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.
- Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
- Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
- Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
- Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
- Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
- Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
Our use of AI within the recruitment process Thomson Reuters utilizes Artificial Intelligence (AI) to support parts of our global recruitment process. Unless you opt-out, our AI system will assess the information provided by you and compare it to the requirements listed for the role, and present the result to our recruitment personnel for further review. The AI system acts as a supporting tool, but there is always a human making the decision if you will be considered for the role.
In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan. Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations.

Eligible office location(s) for this role include one or more of the following: New York City, San Francisco, Los Angeles, and/or Irvine, CA; McLean, VA; Washington, DC. The base compensation range for the role in any of those locations is $146,800 USD - $272,600 USD.
For any eligible US locations, unless otherwise noted, the base compensation range for this role is $127,400 USD - $236,600 USD.
For Ontario, Canada, the base compensation range for this role is $140,000 CAD - $175,000 CAD.

Base pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.
This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.
 About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
Thomson Reuters makes reasonable accommodations for applicants with disabilities, including veterans with disabilities, and for sincerely held religious beliefs in accordance with applicable law. If you reside in the United States and require an accommodation in the recruiting process, you may contact our Human Resources Department at [email protected] . Disability accommodations in the recruiting process may include things like a sign language interpreter, making interview rooms accessible, providing assistive technology, or other relevant accommodations. Please note this email is not intended for general recruitment questions and we will promptly respond to inquiries regarding accommodations. More information on requesting an accommodation here.
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More information about Thomson Reuters can be found on thomsonreuters.com
Salary Context
This $127K-$272K range is above the median for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Thomson Reuters, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($200K) sits 9% below the category median. Disclosed range: $127K to $272K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Thomson Reuters AI Hiring
Thomson Reuters has 31 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Engineer, Data Scientist. Positions span New York, NY, Eagan, MN, US, Brooklyn, NY. Compensation range: $218K - $340K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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