Lead / Staff Full Stack Engineer, AI Platform & Agents

Job Posting

As Lead / Staff 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, mentor less experienced engineers, and lead by example. 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.

TypeScript, Node.js, React, Python, LangChain / LangGraph, MCP / A2A, Rust

AWS (primary), Azure, GCP; Docker, Terraform, GitHub Actions

DocumentDB, DynamoDB, OpenSearch, Azure AI Search

Azure OpenAI, AWS Anthropic, Google Gemini

GitHub, Confluence, Slack

What you’ll do

Design and implement full-stack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.

Build developer tooling, CI / CD, and observability for safe, fast iteration (evals, canaries, rollout / rollback, cost and quality telemetry).

Apply secure SDLC and privacy-by-design practices (threat modeling, least privilege).

Collaborate with product, UX, and domain experts to deliver customer-focused solutions with measurable outcomes.

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.

Lead by example and be heavily hands-on : drive architecture, mentor engineers, and take ownership of larger projects.

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

Director 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.

Minimum qualifications

5+ years of professional software engineering experience.

Strong full-stack development skills and cloud experience

(AWS / Azure / GCP).

Expert in at least one, and proficient across the others :

AI Agent development and evaluation

Backend development

Frontend development

Cloud services (AWS / Azure / GCP)

CI / CD and Infrastructure as Code

Site Reliability Engineering (SRE)

Quality engineering / testing strategy

Secure SDLC and privacy by design

Proven track record delivering secure, reliable, cloud-native systems to

production.

Excellent problem-solving, ownership, and cross-functional

communication.

Nice to have

Proven ability to deliver software products independently or as part of a

small, fast-paced team.

Experience of taking AI agents from concept to production, including safety

evaluations, iterative testing (e.g., A / B testing), and continuous

improvement.

Experience with LangChain / LangGraph and MCP; vector / RAG systems;

OpenSearch.

Worked on traditional ML tasks like training, deployment, and monitoring.

Understand how LLMs work, their failure modes, and techniques like fine-

tuning and model adaptation.

Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.

Stages

15‑minute intro screen

2× live coding in your preferred language

1× systems design

1× presentation of past work

​Timeline : Typically 2–4 weeks

Your first months

Month 1 : Deep-dive into one platform component most aligned with your

expertise; ship small improvements while ramping up.

After onboarding : We’ll align on a high-impact area that fits your strengths

and ambitions.

To apply :

Please submit your resume along with a brief cover letter that includes a “Statement of Exceptional Work.” In your cover letter, highlight one of your most impactful projects by addressing the following :

Your role and the problem space you were working in

The technical and product challenges you faced, and how you addressed them

The measurable impact of your work (e.g., metrics, outcomes, improvements)

This will help us better understand your approach to solving complex problems and the value you bring to the team.

Please do not include any proprietary or confidential information in your submission

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