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Thomson Reuters

Legal, financial data, and media services

AI Staff Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, or equivalent experience is required; a master's degree is preferred.
  • At least 8 years of software engineering experience, including at least 4 years in senior or lead roles on AI/ML systems.
  • A track record as a software engineer with AI expertise rather than primarily as a data scientist or researcher, with hands-on experience in generative AI, retrieval-augmented generation, or large language model-based systems across discovery, architecture, agentic tools, evaluation, deployment, and metrics.
  • Expert-level proficiency in Python or another object-oriented language, with strong backend service and API design skills.
  • A solid understanding of machine learning principles, evaluation methodologies, and distributed systems, plus working experience with AI/ML frameworks such as PyTorch or TensorFlow.
  • Advanced experience with AWS, Docker, Kubernetes, and Terraform, and a record of integrating AI models into large-scale production systems through APIs, data pipelines, and cloud-native architectures.
  • Strong technical leadership and mentoring experience as an individual contributor, with communication skills to influence senior stakeholders.

Responsibilities

  • Build and architect enterprise-scale AI-driven systems, including multi-component pipelines, retrieval-augmented generation and knowledge graph-based architectures, and autonomous AI agents with multi-step reasoning; work hands-on across AI orchestration, retrieval-augmented generation, API gateways, microservices, and modern web user interfaces.
  • Evaluate and drive adoption of emerging AI techniques; run proof-of-concept work and assess technical feasibility for new AI-driven features; monitor AI research and translate insights into technical roadmaps; represent the organization at industry conferences and events.
  • Make architecture decisions and translate business requirements into scalable technical specifications; mentor senior and junior software engineers; champion MLOps and LLMOps practices and governance for the AI model lifecycle.
  • Design and implement testing, monitoring, and observability for AI systems at scale, and ensure compliance with ethical AI principles, security standards, and regulatory requirements.
  • Partner with AI researchers, engineering leadership, design, and product to turn AI capabilities into customer-facing applications; set technical priorities and remain engaged through delivery so AI investments produce measurable business value; optimize latency, cost, and user experience; and influence product strategy through technical depth.

Desired Qualifications

  • Experience leading technical direction for teams building agent-based systems or enterprise integrations with AI APIs such as OpenAI or Anthropic.
  • Advanced knowledge of vector databases, embeddings, semantic search, and information retrieval.
  • Hands-on experience with knowledge graphs, including graph data modeling, ontologies and taxonomies, graph databases such as Neo4j or Amazon Neptune, and combining graphs with large language models through methods such as GraphRAG and entity extraction.
  • Domain expertise in legal, tax, accounting, other regulated industries, or large-scale search platforms.
  • Successful AI product launches and experience scaling AI systems to enterprise customers.
  • Experience with AI governance, model risk management, and regulatory compliance.
  • Publications, patents, or speaking experience in AI/ML.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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