#BETHEDIFFERENCE
If making a difference matters to you, then you matter to us.
As Senior Full Stack Engineer, AI Platform & Agents, you will build the GenAI platform that powers critical decisions in healthcare, legal, tax, and compliance industries. Your work will directly shape the future of these
fields, enabling faster, safer, and more impactful decision-making at a global
scale.
About this role
Our team is building a central GenAI Platform to empower hundreds of product
teams across the organization with scalable capabilities for rapid development,
validation, and deployment of AI agents. We also drive the development of the
most impactful AI agents, ensuring faster delivery and greater impact across
multiple domains. With over 20 agents already launched and many more in
progress, our work accelerates innovation and improves outcomes in critical
industries.
You'll join a 100-engineer remote-first team within a larger organization that
combines the stability of an established company with the agility of a startup. In
this high-autonomy, high-impact role, you'll take problems from concept to
production. You'll design and ship full-stack systems, shape platform capabilities to empower hundreds of product teams, and directly contribute to the
development of the most impactful AI agents.
Flagship Agent: UpToDate Expert AI
In Health, we’re launching UpToDate Expert AI—a medical research and clinical
reasoning agent that transforms the world’s most widely used point-of-care
knowledge resource into a real-time medical assistant. Millions of physicians will rely on it to accelerate differential diagnosis, refine treatment decisions, and
reduce cognitive load—while maintaining rigorous safety, privacy, and guideline
fidelity. Improvements you ship (latency, reliability, hallucination reduction) will
translate directly into faster, higher-quality patient care at global scale.
Tech stack
You don’t need to know all of these on day one, but you should be ready to learn
quickly.
1. TypeScript, Node.js, React, Python, LangChain/LangGraph, MCP/A2A, Rust
2. AWS (primary), Azure, GCP; Docker, Terraform, GitHub Actions
3. DocumentDB, DynamoDB, OpenSearch, Azure AI Search
4. Azure OpenAI, AWS Anthropic, Google Gemini
5. GitHub, Confluence, Slack
What you’ll do
6. Design and implement full-stack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.
7. Build developer tooling, CI/CD, and observability for safe, fast iteration (evals, canaries, rollout/rollback, cost and quality telemetry).
8. Apply secure SDLC and privacy-by-design practices (threat modeling, least privilege).
9. Collaborate with product, UX, and domain experts to deliver customer-focused solutions with measurable outcomes.
10. Apply current LLM patterns (RAG, retrieval, routing, tool-use, evals) to deliver measurable customer value—faster, more reliable AI systems; reduced time-to-decision; improved trust/safety metrics; and lower cost per query.
11. Lead by example through writing high-quality, maintainable code that demonstrates engineering craftsmanship
Team context
Org and Sub-teams: Central GenAI Platform within Wolters Kluwer, driving
innovation across businesses by creating re-usable platform services and
components. Sub-teams are fewer than 10 engineers, focused on platform
services or customer-facing agents.
Culture and Reporting: We value a "manager of one" mindset, where
outcomes matter more than optics. Authority is earned through
demonstrated impact, not tenure or title. You’ll report directly to the VP of
Engineering, AI Platform.
Team Size and Impact: Our globally distributed team of ~100 engineers
combines the stability of an established company with the agility of a
startup. We are moving fast, and there are many areas where you can have
a big impact.
Work setup: Remote-first in US or EU, with hybrid options near major
offices. Collaboration requires 9–11 AM CST overlap. Occasional travel for
team onsites/offsites as needed.
Minimum qualifications
12. 5+ years of professional software engineering experience.
13. Strong full-stack development skills and cloud experience
14. (AWS/Azure/GCP).
15. Expert in at least one, and proficient across the others:
16. AI Agent development and evaluation
17. Backend development
18. Frontend development
19. Cloud services (AWS/Azure/GCP)
20. CI/CD and Infrastructure as Code
21. Site Reliability Engineering (SRE)
22. Quality engineering / testing strategy
23. Secure SDLC and privacy by design
24. Proven track record delivering secure, reliable, cloud-native systems to
25. production.
26. Excellent problem-solving, ownership, and cross-functional
27. communication.
Nice to have
28. Proven ability to deliver software products independently or as part of a
29. small, fast-paced team.
30. Experience of taking AI agents from concept to production, including safety
31. evaluations, iterative testing (e.g., A/B testing), and continuous
32. improvement.
33. Experience with LangChain/LangGraph and MCP; vector/RAG systems;
34. OpenSearch.
35. Worked on traditional ML tasks like training, deployment, and monitoring.
36. Understand how LLMs work, their failure modes, and techniques like fine-
37. tuning and model adaptation.
38. Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.
Your first months
39. Month 1: Deep-dive into one platform component most aligned with your
40. expertise; ship small improvements while ramping up.
41. After onboarding: We’ll align on a high-impact area that fits your strengths
42. and ambitions.