Associate Director, Human/AI Creative Technologist

Kyndryl•Dallas, TX

2d•Onsite

About The Position

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. As the Associate Director, Human/AI Creative Technologist, you will be part of Kyndryl Vital, a global network of designers, engineers, writers, researchers, and strategists. You will drive strategic initiatives and create impactful experiences for the world’s critical systems by combining technical expertise with human-centered design to prototype and implement innovative solutions. Creative technologists blend expertise in code, hardware, and emerging technologies to bring ideas to life. This role is based in our Dallas, TX office and requires candidates to reside in the area or be willing to relocate.

Requirements

Bachelor’s Degree in a relevant field (or equivalent demonstrable portfolio of work).
10+ years of proven work in experience design, creative technology, or innovation roles.
At least several years in a leadership capacity, leading interdisciplinary teams and managing senior-level client relationships.
Experience in multiple industries or a deep focus in one.
Proven track record of delivering large-scale design and technology programs in enterprise environments.
Understanding of enterprise requirements (compliance, scalability, global deployment, etc.) and experience leading projects that navigated these successfully.
Experience in consulting or agency leadership, including responsibilities for account growth or business development.
Strong familiarity with IT governance, security standards, and system integration at a high level.
Experience building or scaling a team or practice (hiring talent, defining team roles, instituting training programs).
Collaboration with Open-Source Agent Stacks: Ability to partner with AI engineers working in open-source agent runtimes and translate experience requirements into tool contracts, UI behaviors, and evaluation criteria without blocking engineering velocity.

Nice To Haves

Hands-on background in technology (software development, data science, etc.) earlier in career.
Advanced degree or certification in design, HCI, computer science, or related (e.g., MDM, MDes, MFA, d.MBA or equivalent).

Responsibilities

Guide large teams in user-centered practices and ensure that complex, multi-touchpoint solutions address fundamental user needs.
Create or approve user experience guidelines and frameworks.
Lead cross-disciplinary teams, collaborating with and orchestrating engineering and other departments.
Resolve conflicts or misalignments between disciplines by refocusing everyone on common goals.
Act as a thought leader in applying emerging technology to solve design and business problems, anticipating relevant technologies or trends (like agentic AI, edge computing, blockchain, etc.) and incorporating them into strategic planning.
Encourage a culture of continuous innovation within the team through innovation sprints or research initiatives.
Utilize deep knowledge of prototyping at scale, setting expectations and processes for teams to prototype efficiently and ensuring rapid experimentation remains a core part of the project approach.
Design interaction patterns for approvals, escalation, rollbacks, and exception handling for human-in-the-loop systems.
Assess technical, operational, and financial feasibility of designs for clients, guiding teams toward innovative yet realistic solutions.
Craft vision narratives, white papers, or executive presentations that frame innovative concepts in terms of business value and strategic necessity.
Establish guidelines or principles for ethical AI and data usage, ensuring solutions are vetted for ethical implications and risks related to bias, privacy, and security are mitigated.
Define cross-team standards for agent tool ecosystems (API patterns, permission models, audit evidence needs, lifecycle/versioning) enabling AI engineers to build and reuse tools safely at scale.
Influence reusable UI patterns and reference implementations for agentic experiences (design system alignment, interaction standards, observability touchpoints).
Establish evaluation standards and reusable QA patterns for agentic engagements.
Define what teams must log/measure for agentic experiences so quality can be managed across programs.
Partner with AI engineers working in open-source agent runtimes and translate experience requirements into tool contracts, UI behaviors, and evaluation criteria.