The Senior Technical Business Analyst – Product Engineering is responsible for translating business objectives into detailed, development-ready technical requirements while enabling modern engineering practices such as Spec-Driven Development, AI-assisted software engineering, and AI-powered product innovation.
This role serves as a critical bridge between Product Management, Business Stakeholders, Architects, and Engineering teams. The ideal candidate combines strong business analysis expertise with technical acumen and the ability to leverage AI tools to reverse engineer existing applications, discover business rules, generate specifications, validate requirements, and support AI-enabled product development.
The individual will play a key role in modernizing how requirements are gathered, documented, validated, and maintained throughout the Software Development Lifecycle (SDLC). They will help establish structured specifications that improve developer productivity, reduce ambiguity, accelerate delivery, and support AI-assisted development workflows.
Key Responsibilities
- Partner with Product Management, Engineering, Architects, UX, and Business Stakeholders to understand business objectives and translate them into actionable technical requirements.
- Elicit, analyze, document, and validate functional and non-functional requirements.
- Create detailed user stories, use cases, business process flows, acceptance criteria, and technical specifications.
- Ensure requirements are complete, traceable, testable, and aligned with business outcomes.
- Facilitate requirement workshops, stakeholder reviews, and backlog refinement sessions.
Spec-Driven Development Enablement
- Author and maintain engineering-ready specifications that can be consumed by development teams, architects, QA teams, and AI-assisted development tools.
- Define detailed functional behaviors, workflows, business rules, data models, integration requirements, and API contracts.
- Create structured specifications that support automated generation of engineering artifacts and development tasks.
- Establish requirement templates, standards, and governance practices for Spec-Driven Development.
- Collaborate with engineering teams to convert requirements into implementation-ready technical work items.
- Drive requirement quality and completeness to reduce delivery risk and rework.
- Utilize AI-assisted tools to analyze and reverse engineer existing applications, workflows, APIs, databases, and business processes.
- Identify undocumented business rules, technical dependencies, workflow variations, and integration patterns.
- Convert legacy functionality into modern technical specifications and future-state requirements.
- Support modernization initiatives by documenting current-state and target-state processes, systems, and architectures.
- Collaborate with engineering and architecture teams to build reusable knowledge repositories and functional documentation.
- Leverage AI tools to accelerate requirement discovery, documentation, analysis, traceability, and validation activities.
- Use AI-powered techniques to generate user stories, acceptance criteria, process flows, test scenarios, and technical specifications.
- Evaluate AI-generated outputs for accuracy, completeness, consistency, and business relevance.
- Develop and refine prompts that improve requirement generation, analysis, and engineering productivity.
- Establish best practices for responsible use of AI throughout the requirements lifecycle.
Prompt Engineering & AI Feature Definition
- Develop structured prompts and workflows for business and engineering use cases.
- Collaborate with Product and AI teams to define requirements for AI-powered product capabilities.
- Create prompts, evaluation criteria, guardrails, and business validation rules for AI solutions.
- Support design and validation of Generative AI, conversational AI, intelligent search, recommendation systems, and workflow automation features.
- Define expected behaviors, user interactions, grounding requirements, and success metrics for AI-enabled experiences.
AI Validation & Quality Assurance Support
- Define business-oriented evaluation criteria for AI-powered applications and features.
- Create validation scenarios, test cases, and benchmark datasets for AI solutions.
- Work with QA and Product teams to validate response quality, accuracy, relevance, safety, and business effectiveness.
- Analyze AI evaluation results and recommend improvements to prompts, retrieval strategies, workflows, and user experiences.
- Establish measurable quality metrics and acceptance criteria for AI-generated outcomes.
Stakeholder Collaboration & Communication
- Collaborate effectively with Product Managers, Architects, Engineering Leads, QA teams, UX Designers, and Business Stakeholders.
- Act as the liaison between technical and business teams, ensuring shared understanding and alignment.
- Present complex technical concepts, product requirements, and analytical findings in a clear and business-friendly manner.
- Support leadership teams with business cases, impact assessments, process improvement opportunities, and product strategy initiatives.
Required Skills & Expertise
- Bachelor’s or Master’s degree in Business, Computer Science, Software Engineering, or a related field.
- 8+ years of experience as business analyst or system analyst
- 3+ years of experience working directly with software engineering teams
- Advanced requirements elicitation and analysis techniques.
- User story creation and backlog management.
- Business process modeling and workflow analysis.
- Requirements traceability and documentation management.
- Functional and non-functional requirement definition.
- Business case development and stakeholder management.
Technical Skills
- Strong understanding of software development lifecycle (SDLC).
- Experience working closely with software engineering and architecture teams.
- Knowledge of APIs, microservices, cloud platforms, system integrations, and modern application architectures.
- Understanding of database concepts, data flows, and system interactions.
- Familiarity with Agile development methodologies and product delivery frameworks.
AI & Modern Development Practices
- AI-Assisted Requirements Engineering.
- Spec-Driven Development.
- Prompt Engineering.
- AI-Oriented SDLC.
- AI Testing and Evaluation Frameworks.
- Generative AI Product Development.
- Reverse Engineering and Documentation Automation.
- Developer Productivity Platforms and AI Coding Assistants.
- Experience with GitHub Copilot, OpenAI ChatGPT, Claude, or similar AI-enabled engineering tools.
Analytical & Communication Skills
- Strong analytical and critical-thinking capabilities.
- Ability to transform complex business problems into structured requirements.
- Excellent written and verbal communication skills.
- Strong facilitation and stakeholder management abilities.
- Experience leading workshops and requirement discovery sessions.
Preferred Qualifications
- Experience supporting enterprise SaaS products and digital platforms.
- Exposure to AI-powered product development and evaluation processes.
- Experience with modern product management and engineering collaboration tools such as Azure DevOps, Jira, Confluence, Miro, and GitHub.
- Experience with process mining, application modernization, or legacy platform transformation initiatives.
- Experience creating specifications that directly support AI-assisted software development.
Our Interview Practices
To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
Compensation:
$71,300.00 - $124,500.00 USD
This role is eligible for Bonus.
Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.
Additional Information:
Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.
