About Client

Our client builds recruiting software for enterprise employers: for recruiters, for hiring managers and for candidates, used by some of the largest employers in North America. Our customers hold us to enterprise standards on security, compliance and accessibility.

Why this role exists

Agentic AI is changing how we build software, what our software does, and how hiring itself works.
How we build. Our engineers write specifications and review code. AI agents build a growing share of our changes, and AI and human reviewers check every one. An agent’s work is only as good as the standards and specifications it builds from.
What we build. Recruiters, hiring managers and candidates increasingly hand work to AI agents, inside our products and from their own assistants: sourcing and matching on skills, screening, interviewing, scheduling, following up. Candidates apply with AI too, and regulators expect people to know when AI is involved and to be able to reach a person. The experience becomes a working relationship: what the person asks for, what the agent does, whether the person can trust it, and how they step in when it is wrong.
This role shapes all of it. You will modernize the products customers use today, evolve the AI assistant already live in them and define what comes next, and set the standards people and agents build from. You will work consultatively across product, engineering and customers, and you are key to our client’s transformation.

What you will do

Design how people and agents work together

  • Design delegation end to end: how a person states intent, sets limits, reviews what the agent did and why, corrects it, and takes back control.
  • Define how the agent behaves: what it says, when it asks, and when it stops.
  • Make agent work visible and trustworthy through confidence signals, explanations, audit trails and recovery from errors, and guard against people approving agent work unchecked as well as ignoring it.
  • Choose between conversational, proactive, in-workflow and traditional interfaces for each job, including experiences shown inside AI assistants and agents acting for candidates or recruiters, and combine them into one experience.
  • Keep a person meaningfully accountable for every decision that affects a candidate, including who is screened out.
  • Make AI use clear in every product: people know when AI is involved, how it contributed to an outcome, and how to ask a person to review it, configurable by jurisdiction.
  • Design the controls customer administrators use to set what agents may do on their own.

Modernize the current products

  • TalentBench: shift recruiters from doing each step to supervising agent work across many roles, with exception queues, batch review and clear hand-offs, and make the remaining workflows faster with fewer errors.
  • TalentConnect: give hiring managers a fast, clear way to review candidates and return their input.
  • TalentCommunity: meet the expectations candidates bring from consumer apps: mobile first, fast and accessible. When an agent screens, interviews or messages candidates, they know it is AI, know where they stand, and can reach a person.
  • Design for AI on the candidate side: high volumes of AI-written applications, candidates’ own agents, and identity checks that don’t penalize genuine applicants.
  • Bring every product to a consistent standard, holding WCAG 2.2 AA across customer-branded themes in multiple languages.
  • Set design priorities across all products, current and new, with the VP, AI and Transformation, so no team waits on design: the standards and specifications carry design decisions without you in every loop.

Own the UX standards

  • Own written UX standards and design system (patterns, components, content and accessibility), working within our architecture decisions, precise enough that agents build to them consistently.
  • Add agentic patterns as we learn them, informed by AI-in-hiring regulation and emerging industry practice.
  • Update the standards whenever research or a release teaches us something new, and check that what ships still matches them.

Prototype, prove and specify

  • Explore many directions in hours, put prototypes in front of users within days, and converge.
  • Build technical proofs of concept with engineers to test feasibility and safety before work reaches the roadmap.
  • Write specifications and acceptance criteria an agent can build from, with the working prototype as the reference, and review the result with product before release approval.

Ground decisions in evidence

  • Apply the science of UX, not only the craft: controlled usability studies, task analysis and measurement.
  • Define what good agent output looks like, as quality criteria and test cases the team uses before and after release.
  • Measure experience quality, including how often people accept, edit or override an agent’s work, whether that reliance is warranted, and whether outcomes stay fair across candidate groups.
  • Start from what we already know: support tickets, analytics and customer feedback.
  • Join customer meetings to hear feedback first-hand, gather ideas and test concepts.

Lead the change

  • Present and defend design direction to executives, product, engineering and customers with evidence, and change course when the evidence says so.
  • Track how agentic technology, UX practice, competitors, regulation and the recruiting industry are changing, and turn what matters into standards and decisions.
  • Raise the team’s skill in agentic experience design through reviews and examples, and help it adopt better methods and tools as they emerge.

What you bring

Required

  • Six or more years in product or UX design, including enterprise B2B SaaS web applications.
  • Hands-on experience designing AI-powered or agentic experiences, and a clear point of view on how people and agents should work together.
  • A record of staying current and evolving quickly: you adopt new methods and tools as AI, the industry and customer needs change, drop what stops working, and can show the effect on your work.
  • An understanding of how agentic AI changes the way software is built, and experience writing specifications or standards that agents build from.
  • Able to prototype in working code with AI assistance, and to make front-end changes for an engineer to review.
  • An evidence-based research practice: usability testing, journey mapping, competitor analysis and measurement.
  • Experience owning or shaping a design system or UX standards across more than one product, including customer-branded, multilingual products.
  • Working knowledge of the Web Content Accessibility Guidelines (WCAG) 2.2 at level AA.
  • Experience designing AI for regulated contexts: explaining how AI contributed to an outcome and how a person can request human review.
  • A consultative way of working with customers, engineers and executives: listening for the real need, testing ideas with the people affected, and presenting and defending decisions.
  • Clear, precise writing that both people and agents can act on.

Nice to have

  • Led a product through a major platform or interaction-model transition.
  • Recruiting, HR technology or marketplace products.

Your first 90 days

By You will have
Day 30 Met users of each product and joined customer conversations. Audited the current experience, the live AI assistant and the standards, and shared where to start.
Day 60 Designed and tested an agentic experience for a live initiative, with a user-tested prototype and an engineering proof of concept. Added the first agentic patterns to the standards, and seen a design change reach production.
Day 90 Presented an experience direction for current products and the agentic future to executive leadership, including how we measure agent quality and fairness, and set next-quarter design priorities with the VP, AI and Transformation.

How we work

Every change to production passes two human gates: code review and release approval. We use AI tools every day in every role, and we expect you to lead us in your domain.

Applying

Send your resume. If you move forward, be prepared to present:

  • An AI-powered or agentic experience you designed, and how you decided what the person controls and what the agent does.
  • A research project, the decisions it led to, and how you measured the result.
  • A prototype or proof of concept you built with AI tools.
  • A design standard you created or evolved.
  • A recent method or tool you adopted to stay current, and why.

The pay range that the employer reasonably expects to pay for this position is between ¤140,000 and ¤175,000

Our voluntary benefits offering includes medical, dental, vision and retirement benefits.

This posting is for an existing vacancy.

If you believe this post to be fraudulent, please report by clicking here Tundra Technical Solutions is a global workforce and technology delivery firm, ranked by Staffing Industry Analysts as one of the largest in North America. At Tundra, we aren't just hiring top talent at the world's most recognizable brands; we are pioneers of social recruitment. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other legally protected characteristics. We welcome and encourage diversity in the workplace.

We use artificial intelligence tools to help our recruiters screen and assess talent. These tools do not replace human decision making in the process.

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