Senior Creative Technologist: Prototyping Human‑AI

Kyndryl

Greater London

Hybrid

GBP 70,000 - 100,000

Full time

14 days+

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Job summary

Kyndryl is seeking a Senior Creative Technologist to drive the end-to-end prototyping workflow from brief to service blueprint, including user research, real-world testing, and hands-on building across interfaces, devices and AI agents.

You will own customer-facing engagements, develop rapid prototypes, and collaborate with design, engineering and research teams to demonstrate credible, end-to-end experiences. The role emphasizes rapid delivery and evidence-based iteration.

Qualifications

Education - Bachelor's degree in interaction design, HCI, industrial design, computer science, engineering, architecture or another creative or technical discipline, or equivalent practical experience.
Experience - 5+ years in creative technology, design technology, interaction design or software prototyping, including 2+ years building prototypes for customers or stakeholders under time pressure.
Portfolio - A link or PDF of recent work showing prototypes you built yourself, the question each one answered and what changed as a result - not only strategy decks or polished screens.
Language - Business-level fluency in English.

Responsibilities

Make the brief buildable - Turn a customer opportunity into users, workflows, decisions, constraints and hypotheses. Map the service blueprint and the human-agent-system model: roles, knowledge, handoffs, exceptions and what should stay human.
Prototype at the lowest useful fidelity - Move from sketches and Wizard-of-Oz simulations to coded interfaces, live agents, connected devices or fabricated forms as the question demands. Put the perceived experience first and fake what is not needed to answer it.
Make it behave for real - Wire approved or synthetic data, APIs, models and tools so prototypes show credible end-to-end behaviour rather than disconnected screens.
Test with people before polishing - Run focused research and co-design with customers, users and subject‑matter experts. Define the evidence up front, then diagnose whether a breakdown sits in the interaction, workflow, policy, data or model.
Work directly with customers - Present and demonstrate your work to customer teams, lead research, co‑design and testing sessions, and bring tangible work into executive workshops. On smaller engagements, act as the customer's day-to-day contact with direction from the Associate Director or Director.
Capture the pattern behind the prototype - Separate reusable interaction logic, components, agent states, prompts, policies and evaluation assets from the customer‑specific example.
Package the work to move - Hand pilot and delivery teams the flows, code, assets, dependencies, risks and test evidence they need to continue without starting over.
Explore the edge - Experiment with sensors, microcontrollers, edge devices, fabrication and ambient feedback, and use the Lab's protected moonshot capacity to test high‑upside ideas in human‑AI collaboration.
Scope and partnerships - You own the making within an engagement - the quality, credibility and learning value of the prototypes and artifacts you carry - and the day-to-day customer relationship on smaller engagements. The senior executive relationship sits with the Associate Director and Director.
You own assigned workstreams and prototypes - Day-to-day design, technical exploration, build, testing, evidence and handoff, and the customer sessions that go with them.
The Associate Director and Director set engagement direction - Customer journey, executive relationship, opportunity framing, prioritization and post‑Lab outcome. On smaller engagements you carry the customer relationship within that direction.
Engineering and Lab operations own their domains - Engineering leads own production architecture, security, integration and deployment; you own prototype behaviour and the intended human‑AI experience. Scheduling, hospitality, AV, safety and equipment sit with Lab operations.
Success looks like - Customers experience and question the opportunity before major investment; testing visibly changes the design; delivery teams continue the build and other Lab teams reuse the patterns, assets and evaluation methods behind it.