Capability Experience Designer (UX) Technology

FIS Global•Jacksonville, FL

About The Position

Every day at FIS, innovators, problem-solvers and changemakers work together to create technology that advances the world of finance. We embrace new ideas, challenge what's possible, and empower our teams to make a lasting impact. If you're ready to help shape the future of fintech — Unlock your next chapter with FIS. About the role: This is not a traditional design role. As Capability Experience Designer for Engineering & Infrastructure, you will sit at the intersection of how engineers work and how they grow — designing the experiences, tools, and enablement systems that help FIS engineers adopt Agentic AI, operate modern infrastructure, and develop the skills to thrive in a human + digital workforce. You will work across the Engineering Service Delivery lifecycle — from onboarding and agentic code review through to platform operations, SRE practices, and cloud-native working — designing solutions that are embedded in the workflow, not layered on top of it. Your design canvas is the engineer's daily reality: their IDE, their runbooks, their deployment pipeline, their on-call rotation.

Requirements

Bachelor's degree or equivalent in UX Design, Human-Centered Design Thinking, Learning Experience Design, Computer Science or related field.
Proven experience designing enablement, learning, or behavior-change solutions within engineering, technology, or infrastructure organizations.
Strong UX fundamentals: journey mapping, workflow analysis, service design, interaction design, and prototype-and-test methodologies.
Understanding software engineering delivery practices — familiarity with how engineers work, how code moves from idea to production, and where friction lives in developer workflows.
Experience translating complex technical or organizational change into practical, intuitive experiences for technical audiences.
Ability to conduct user research with engineers and turn insights into rapid, iterative improvements.
Strong collaboration, facilitation, and stakeholder management skills across both technical and non-technical

Nice To Haves

Experience supporting Agentic AI, developer tooling, or AI platform adoption programs.
Familiarity with Platform Engineering, SRE, or Cloud operating models and the roles within them (SRE, Platform Engineer, Cloud Architect, DevOps).
Industry expertise in Banking, Payments, Cap Market, Finance
Knowledge of developer experience (DX) design principles and toolchain-embedded enablement approaches.
Experience creating capability frameworks, role taxonomies, or learning architecture for engineering populations.
Familiarity with digital adoption tools, in-workflow learning, and performance-support design patterns.
Understanding of AI-enabled or personalized capability solutions within enterprise engineering contexts.
Experience facilitating workshops or capability discovery sessions with senior engineering or infrastructure leaders.

Responsibilities

Design the end-to-end engineer experience for adopting Agentic AI tools — from first awareness through to confident, productive use in day-to-day delivery.
Map the Engineering Service Delivery lifecycle and identify the moments where enablement, guidance, and skill-building have the highest impact.
Build intuitive onboarding journeys for Agentic AI capabilities: AI Gateway, Agent Runtime, SDK standards, and agentic code review workflows.
Design the Human ↔ Digital Worker task boundary experience — helping engineers understand what to delegate, when to escalate, and how to maintain accountability.
Prototype and iterate enablement touchpoints (in-workflow nudges, contextual guides, decision aids) using adoption signals and engineer feedback.
Design capability experiences for Platform Engineering, SRE, and Cloud operating model roles — from self-serve platform consumption to on-call readiness and incident response.
Create workflow-embedded enablement for engineers onboarding to the Central AI Gateway, Agent Runtime, and cloud-native infrastructure patterns.
Map SRE and Platform Engineering journeys: identify friction points, knowledge gaps, and moments of need where targeted enablement changes outcomes.
Build scalable assets — runbook templates, decision frameworks, escalation guides — that embed good practice into infrastructure operations rather than asking engineers to context-switch into a learning system.
Partner with Platform and SRE leads to design operating rhythm tools that support the shift from activity-based to outcome-based performance.
Translate the Diamond-shape Talent Model (Thought Leadership + Dev + Action) into concrete learning pathways, role profiles, and progression criteria for AI-era engineering roles.
Design the Capability & Learning session framework for Workstream 2 — facilitating structured capability discovery across engineering and infrastructure populations.
Build the Learning Management and Knowledge System architecture that Group C identified: validation approach, applied learning, and judgment development in the flow of work.
Use engineer performance, adoption, and platform usage data to continuously evaluate capability gaps and refine solutions.
Maintain enterprise-wide design standards and reusable patterns across engineering academies, platforms, and channels.
Work directly with Engineering leadership, Platform teams, SRE leads, AI Platform Program owners, and Workforce Design to ensure capability solutions are grounded in real delivery context.
Conduct ongoing user research with engineers — shadowing workflows, running feedback loops, and translating insights into improvements rapidly.
Audit and optimize existing enablement materials for cognitive load, relevance, and usability within engineering contexts.
Ensure all solutions are accessible, inclusive, and designed for the diverse range of engineering roles and seniority levels across FIS.