Senior Product Software Engineer

Wolters Kluwer•New York, NY

1d•Hybrid

About The Position

Take your software engineering career to the next level as a Senior Product Software Engineer. You will play a key role in designing, developing, and troubleshooting software programs. Your technical skills and innovative mindset will contribute to the continuous improvement of our products, making a significant impact on user experience and satisfaction. Hybrid: Eight days a month we come together in the closest office (NYC) within 50 miles to experience the value of connecting with colleagues. You will report to the Director, Product Software Engineering and work under the leadership of the VP, Product Software Engineering, DXG FCC CT. This role is a part of DXG | FCC CT Corporation - Wolters Kluwer. Please view the site office location directory for potential office preferences nationwide. | https://bit.ly/Find_A_WK_Office | #LI-Hybrid Division/BU About Us: https://www.wolterskluwer.com/en/about-us/organization | https://www.wolterskluwer.com/en/about-us/organization/financial-and-corporate-compliance Must be legally authorized to work in the United States without employer sponsorship, now or in the future.

Requirements

5yrs minimum in role plus 1yrs (Agentic AI)
Advanced Technology Adoption and Utilization: AI Tool Proficiency: Evaluate and optimize AI tool usage for team efficiency and productivity; AI Output Validation: Establish validation standards and review processes for AI-generated code; Responsible AI Usage: Lead responsible AI initiatives and establish team best practices; Agentic Workflow Design: Design and optimize AI agent workflows for team efficiency.
Programming: The ability to design, write, test, debug, and maintain the instructions, also known as code, that a computer must follow to execute a task. This skill often involves various programming languages such as Python
Competencies: Analytical Skills | Inclusive Collaboration | Drive to Perform | Accountability | Functional Expertise | Operational Expertise
Software Engineering: The ability to design, develop, and maintain software systems and applications by applying principles and techniques of computer science, engineering, and mathematical analysis. This includes the capacity to understand user requirements, create and test the software, and resolve any software-related issues.
Software Development: The ability to design, write, test, and implement software programs, applications, and systems. This includes understanding various programming languages, software architecture, and software testing methods. It also involves problem-solving capabilities to fix software issues and improve functionality.
Problem Solving: The ability to understand a complex situation or issue and devise a solution by defining the problem, identifying potential strategies, and ultimately choosing and implementing the most effective course of action.
Analysis: The ability to examine complex situations or problems, break them down into smaller parts, and understand how these parts work together.
Testing: The skill of evaluating a system or process, often in software or product development. It involves the ability to identify problems, measure effectiveness, and ensure quality or functionality.
Agile: The ability to swiftly and effectively respond to changes, with an emphasis on continuous improvement and flexibility. In the context of project management, it denotes a methodology that promotes adaptive planning and encourages rapid and flexible responses to changes.
Source Code Repository: The ability to effectively use a source code repository, a file archive, and a web hosting facility where a large amount of source code, for software or for web pages, is kept, either publicly or privately. This skill involves the ability to manage and track changes to code, identify and fix issues, merge code from different branches, and collaborate with other developers.
Relational Database: The ability to design, implement, and manipulate a relational database, a type of database that stores and organizes data in a structured way and where data is logically interrelated. This skill often requires proficiency in SQL, database management systems, and an understanding of database design principles.
APIs: The ability to design, develop, and manage Application Programming Interfaces, which constitute the set of protocols and tools used for building application software. This skill includes the capacity to create and maintain high-quality API documentation, implement API security practices, and understand API testing techniques. Additionally, having this ability means understanding how APIs enable interaction between different software systems, allowing them to communicate with each other.
Design: The ability to create, conceptualize, sketch, and implement layouts, structures, and plans either for aesthetic or functional purposes. This could be used in various contexts such as architecture, fashion, graphics, interior, and more. It involves creativity, problem-solving, and strategic thinking.
Framework: The ability to understand, utilize, design, and develop complex structures and systems in various contexts such as programming, project management, or business strategy. This ability requires critical thinking, problem-solving skills, and attention to detail.
Documentation: The ability to create, manage, organize, and maintain important information and documents in various physical and digital formats. This skill may include preparing reports, managing files, storing data, and keeping records organized and updated for easy retrieval and understanding.

Nice To Haves

Knowledge of LLM architecture, inference, context limits, and cost/latency tradeoffs.
Mastery of agent prompting frameworks like ReAct, Chain‑of‑Thought, structured outputs (JSON), and multi-step reasoning patterns.
Experience building agentic RAG systems (iterative retrieval, self‑evaluation, strategy switching).
Hands‑on experience with LangChain, AutoGen, CrewAI, or similar agentic frameworks.
Familiarity with multi-agent orchestration, tool use, and autonomous workflow design.
Understanding of agent ecosystem components: reasoning engines, memory systems, tool interfaces, and goal management.
Proficiency with ML frameworks (TensorFlow, PyTorch) and reinforcement learning concepts.
Experience implementing LLMs with vector databases, embeddings, and RAG pipelines.
Ability to evaluate model performance, mitigate hallucinations, and design safe action loops.

Responsibilities

Lead Software Development: Take the lead in designing, developing, and maintaining complex software applications to meet project requirements.
Design Collaboration: Collaborate with cross-functional teams to define design specifications and details, taking into account diverse perspectives.
Effective Communication: Regularly communicate project updates, progress, and challenges to stakeholders and team members.
Technical Documentation: Prepare detailed technical specifications and requirements documents to guide the development process.
Performance Optimization: Identify bottlenecks and optimize software programs to improve overall performance and efficiency.
Application Design: Lead the design of innovative and user-friendly software applications that align with customer needs and industry standards.
Testing Strategies: Create comprehensive testing routines and procedures to ensure the reliability and accuracy of software applications.
Applied Problem Solving: Utilize mathematical principles and statistical approaches to solve intricate problems in scientific or applied fields within software projects.
Issue Resolution: Collaborate with others to troubleshoot and resolve complex information technology issues that may arise during development.
Data Preparation: Prepare and preprocess data for analysis, ensuring its accuracy and readiness for use in software applications.
Technical Support: Provide technical support to end-users, including assistance with software maintenance, troubleshooting, and usage queries.