Lead / Staff Full Stack Engineer, AI Platform & Agents

Wolters Kluwer; Kingston; Remote; GBP 70,000 - 90,000; Full time

Job summary

A leading technology company in the United Kingdom seeks a Lead / Staff Full Stack Engineer to develop the GenAI platform vital for healthcare, legal, tax, and compliance sectors. In this role, you will mentor engineers and design full-stack solutions, driving impactful changes to improve decision-making processes. Join a dynamic remote-first team, combining the security of an established firm with the agility of a startup.

Qualifications

• Strong full-stack development skills and cloud experience.
• Proven track record delivering secure, reliable cloud-native systems.
• Excellent problem-solving, ownership, and cross-functional communication.

Responsibilities

• Design and implement full-stack applications enabling rapid AI agent development.
• Lead by example and mentor less experienced engineers.
• Collaborate with product and UX teams to deliver customer-focused solutions.

Skills

Full-stack development

Cloud services (AWS/Azure/GCP)

Problem-solving

Cross-functional communication

AI agent development

Quality engineering/testing strategy

Education

5+ years of professional software engineering experience

Tools

TypeScript

Node.js

React

Python

AWS

Docker

Job description

#BETHEDIFFERENCE

If making a difference matters to you, then you matter to us.

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, proficient across 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.

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.