• Develop and integrate LLM-based solutions using platforms such as OpenAI, Microsoft Azure AI, and AWS AI/ML; • Build, orchestrate, and maintain intelligent agents and multi-agent systems applied to various business domains; • Design and implement automation flows and AI pipelines using TypeScript and JavaScript; • Apply prompt engineering techniques to optimize the performance and reliability of language models in production; • Integrate external tools and services via protocols like MCP (Model Context Protocol) and REST APIs; • Collaborate with product, data, and leadership teams to identify AI opportunities and translate business objectives into technical solutions; • Ensure the quality, traceability, and security of implemented AI solutions, following software engineering best practices; • Stay up to date with trends in the AI ecosystem (models, frameworks, tools) and propose continuous improvements to existing solutions.

Senior Software Engineer, Agentic AI Hybrid Canada, Toronto, Ontario Full time JREQ194264 Senior Software Engineer, AI Are you ready to shape the future of AI-driven content technology while leading cutting-edge innovation in a mission-critical role? Do you thrive in environments where your technical expertise can directly impact how the world's leading professionals access and utilize information? We are seeking a talented, self-driven and highly motivated Software Engineer, AI to join the Corporates Tax and Trade team in Toronto. In this role, you will develop scalable and innovative solutions using AI and Machine Learning on a rapidly growing line of products. You will work closely with Product Management, Technology and our Labs teams to enable our customers to build successful AI driven features and products to take their business to the next level. About the Role In this opportunity as Senior Software Engineer, AI you will perform the following responsibilities Development & Implementation - Develop and maintain AI/ML features under the guidance of senior team members - Implement machine learning models and integrate them into software applications - Write clean, well-documented code following established coding standards - Participate in the full software development lifecycle for AI/ML projects - Assist in building data pipelines and preprocessing workflows - Support model deployment and monitoring activities Collaboration & Growth - Work closely with senior engineers to understand AI/ML system architecture - Collaborate with data scientists to implement proof-of-concept models - Participate in code reviews and incorporate feedback to improve code quality - Attend team meetings and contribute to technical discussions - Document development processes and create technical specifications - Stay updated on AI/ML trends and technologies through continuous learning Performance & Optimization - Monitor and optimize model performance, latency, and resource utilization - Implement A/B testing frameworks for AI/ML features - Debug and troubleshoot complex AI/ML systems in production environments - Ensure models are robust, reliable, and perform well at scale - Software Engineering Excellence: - Write clean, well-tested, and maintainable code in Python (or other relevant languages). - Develop and integrate RESTful APIs and microservices to expose AI/ML capabilities to internal and external systems. - Implement robust monitoring, logging, and alerting for AI/ML models and systems in production. - Optimize model inference for speed and efficiency. - Contribute to the full software development lifecycle, from requirements gathering and design to deployment, monitoring, and maintenance. Technical Foundation - Programming Languages: Proficiency in Python; familiarity with Java, JavaScript, or C++ is a plus - ML Basics: Understanding of fundamental machine learning concepts and algorithms - Frameworks: Basic experience with at least one ML framework (TensorFlow, PyTorch, scikit-learn) - Software Development: Knowledge of version control (Git), testing, and debugging - Data Handling: Experience with data manipulation using pandas, NumPy, or similar libraries - Databases: Basic SQL knowledge and understanding of database concepts About You You're a fit for the role of Senior Software Engineer, AI if you have the following required qualifications: Educational Background - Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field - Proven experience designing, building, and deploying production-grade agentic AI workflows — including multi-step reasoning, tool/API orchestration, and LLM-as-judge or eval-driven quality gates — serving real end users at scale. - Coursework or projects involving machine learning, statistics, or data analysis - Understanding of software engineering principles and object-oriented programming - 1+ years of professional software development experience - Professional, academic or personal projects demonstrating AI/ML implementation - Experience in software development or data science (preferred) - Experience with cloud platforms (AWS, GCP, Azure) is a plus 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 (2-3 days a week in the office depending on the role) 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. For Ontario, Canada, the base compensation range for this role is $100,000 CAD - $145,000 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.

• Define the technical vision and architecture for AI and ML solutions, including LLM based applications, conversational voice AI, chatbot platforms, and AI augmented BI systems • Oversee development of training data pipelines and datasets for fine tuning, evaluation, and inference at enterprise scale • Establish enterprise standards for model performance monitoring, drift detection, retraining, and lifecycle governance • Drive implementation of vector embeddings, semantic search, and AI orchestration frameworks • Provide engineering leadership for backend services (APIs, microservices) enabling scalable AI capabilities across the enterprise • Oversee development of scalable data pipelines supporting ingestion, transformation, and real time inference workloads • Drive integration of AI capabilities into enterprise platforms, including customer facing voice and chat systems and internal analytics environments • Ensure solutions meet enterprise standards for scalability, reliability, performance, and security • Define and govern model lifecycle management practices including versioning, deployment, rollback, and compliance • Lead the development of enterprise AI platforms and infrastructure for model hosting, orchestration, and scaling • Establish CI and CD standards and deployment frameworks for AI systems across engineering teams • Build and oversee observability layers to monitor system performance, model behavior, and operational health • Set direction for AI safety and responsible AI practices, including guardrails for bias mitigation, hallucination reduction, and policy adherence • Set and drive enterprise AI strategy aligned to technology vision, platform evolution, and long-term organizational priorities • Lead alignment across a highly matrixed organization, influencing engineering, product, analytics, and business leadership • Serve as a trusted advisor to executive leadership, communicating AI strategy, technical trade-offs, risks, and business impact • Own AI investment strategy, including prioritization, funding alignment, and resource allocation across initiatives • Drive enterprise-wide AI adoption by establishing scalable enablement models across engineering and business teams • Define and execute capability uplift strategies, including upskilling engineers, promoting best practices, and enabling self-service AI development • Champion innovation by introducing emerging AI technologies, tools, and solution patterns to accelerate experimentation and delivery • Establish and govern AI vendor and partner strategy, including evaluation, selection, negotiation, and performance oversight • Oversee SOW development and partner with product and finance leadership to manage budgets, forecasts, and investment planning • Act as the primary interface between engineering and executive leadership, ensuring transparency, accountability, and delivery outcomes • Influence enterprise architecture, engineering standards, and AI governance frameworks

• Design, build, and operationalize agentic AI capabilities for clinical imaging clinical trials • Partner with Product, Imaging Ops, Data Engineering, QA, Security, and Regulatory/Quality to identify high-value automation opportunities • Translate clinical-trial imaging workflows and PDLC processes into agent-ready task models • Work with SMEs to define quality rubrics and human review workflows • Support change management with clear UX patterns, onboarding, and documentation • Promote engineering best practices for agentic systems • Build agentic workflows that support imaging trial processes • Implement retrieval-augmented generation (RAG) patterns • Develop evaluation harnesses for agent behavior • Package and deploy agentic services • Ensure safe production operations and build observability for agentic services