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About This Role
Job Description:
We're looking for a Lead Product Software Engineer - AI to join InnovateHub, our startup-within-the-enterprise that co-designs AI solutions with customers across Wolters Kluwer's Tax and Accounting product portfolio. You'll develop cutting-edge AI features that transform how accounting professionals work, focusing on real customer problems rather than technology-first solutions.
InnovateHub operates with close collaboration between engineers, product managers, UX designers, and researchers. Engineers deeply understand business problems, product managers rapidly prototype ideas, and designers and researchers translate user needs into elegant, evidence-based solutions. We work in fast feedback cycles, obsess over customer value, and blur traditional role boundaries to focus on solving the right problems. We practice Agile and XP methodologies with weekly sprints, BDD/TDD practices, and pair programming with daily rotation to support high team cohesion and knowledge sharing.
This role is ideal for someone who adapts quickly to new technologies, communicates effectively across teams, thrives in collaborative environments, and is passionate about human-centric AI solutions that deliver real value to professionals.
Key Responsibilities:
Customer-Centric Product Development: Co-design AI solutions with customers, focusing on real problems rather than technology-first approaches. Build human-centric AI features that deliver measurable value in fast feedback cycles.
Cross-Portfolio Innovation: Work across TAA's product portfolio, enabling other teams while building AI solutions that can be applied to multiple products and customer segments.
Technical Leadership: Design and implement AI features using Python and modern frameworks. Build intelligent document processing, automated workflows, and AI-powered analytics with a focus on security, product experience, and scalability.
Close Collaboration: Work in InnovateHub's collaborative model where engineers understand business problems as deeply as technical solutions, partnering closely with product managers who prototype their own ideas.
Requirements:
Technical Foundation:
- 5+ years building software applications (experience with Python, JavaScript/TypeScript preferred)
- 1+ years hands-on experience with LLMs or AI systems (NLP preferred)
- Full-stack development capabilities
- Experience with Agile/XP practices including TDD/BDD and pair programming
- Proficiency with AI coding tools (GitHub Copilot, Cursor, or similar)
- Regular use of GenAI utilities (ChatGPT, Claude, etc.) for development workflow
Technical Project Leadership:
- 3+ years leading complex technical projects from inception to delivery
- Experience working in startup-like environments or innovation teams
- Comfort working in collaborative, fast-paced Agile environments with weekly sprints and blurred (but aligned) role boundaries
AI/ML Experience:
- Working knowledge of AI/ML frameworks (LangChain, Hugging Face, OpenAI APIs)
- Experience with vector databases and embeddings
- Understanding of prompt engineering and AI optimization
Communication Skills: Ability to explain technical concepts to non-technical stakeholders and drive adoption of new technologies across teams.
Preferred Qualifications:
- Microsoft Azure AI-102 certification is highly desired - our team is 100% certified and we value this demonstration of Azure AI expertise
- Experience with Azure AI services, advanced AI frameworks, or multi-modal AI systems
- Background in dynamic environments like startups, innovation teams, or product-focused companies that prioritize customer co-design and rapid value delivery
- Experience with document processing, financial data analysis, or B2B professional software
- Experience with MLOps, AI governance, or cross-portfolio AI implementations, particularly in regulated/compliance-driven environments
Our Culture:
At Wolters Kluwer, our core values—Focus on Customer Success, Make it Better, Aim High and Deliver, and Win as a Team—guide everything we do. We are committed to driving success for our customers by delivering innovative solutions that exceed expectations. We continually strive to improve our processes and products, aiming for excellence in all our efforts. Collaboration and teamwork are central to our culture, enabling us to achieve great results together.
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:
$104,800.00 - $183,700.00 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.
Salary Context
This $104K-$183K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 198 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 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Wolters Kluwer, 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 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($144K) sits 34% below the category median. Disclosed range: $104K to $183K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Wolters Kluwer AI Hiring
Wolters Kluwer has 4 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span Cape Girardeau, MO, US, Alphen aan den Rijn, South Holland, Netherlands, New York, NY. Compensation range: $145K - $183K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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