NTT Data Aivista
Member of Technical Staff - Product Design [Bellevue, WA]
Bellevue, WA · Staff+
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$3,104 more — $143,104 — moves this role to Level II and 2 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $143,104 would place this position at wage Level II. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Seattle-Tacoma-Bellevue, WA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- Designing these systems requires more than creating an intuitive interface.
- It requires defining how humans and AI agents work together when decisions have real business, financial, and regulatory consequences.
- Our first product is AI for Insurance, powered by AIVista.
Responsibilities
- Own the human-AI interaction model for AIVista's core workflow patterns, starting with AI for Insurance.
- Design interaction patterns for human-agent and agent-to-agent workflows, including confidence signals, human-in-the-loop controls, permissions, escalation paths, and auditable decision histories.
- Design the tools and experiences that enable builders to author, configure, and operate AI agents.
- Partner with Product, Engineering, and Applied Science to translate complex enterprise workflows into scalable product experiences.
- Build functional prototypes using AI-native and agentic development tools to test interaction models against real model behavior.
- Own and evolve AIVista's design system as product infrastructure, including components, interaction patterns, accessibility standards, and machine-consumable rules.
- Develop a deep understanding of where work between people and agents breaks down across AIVista's customer workflows.
- Get your first journey specifications implemented and build a working prototype that resolves an important behavioral or interaction question.
Requirements
- Deep experience in AI products or regulated, high-consequence workflows, ideally both, including agents, copilots, intelligent automation, human-in-the-loop systems, or comparable products.
- Experience conducting direct customer discovery and translating firsthand understanding of user workflows into product decisions.
- Experience writing specifications and acceptance criteria that engineering teams can execute with minimal clarification.
- Ability to operate effectively in a fast-moving environment with significant ownership and ambiguity.
Nice to have
- Experience designing AI-driven or probabilistic products, including agents, copilots, intelligent automation, or human-in-the-loop workflows.
- Experience designing for trust, accountability, AI governance, and oversight, including explainability, decision provenance, confidence signals, and override paths.
- Experience with spec-driven development, machine-consumable design systems, or accessibility for dynamic and AI-generated interfaces.
- Enterprise client-facing experience with senior operations and technology leaders.
- You don't need to match every qualification.
- If this work excites you and you believe you can do it, we want to hear from you.
Compensation
- The estimated annual base salary range for this role is $140,000-$225,000 USD.
- The salary for the successful applicant will depend on job-related factors such as education, training, work experience, business needs, and market demands.
- Total compensation also includes variable pay in the form of an annual target bonus and other cash incentives, with a combined potential of up to 50% of base salary.
Benefits
- Medical, dental, and vision insurance
- HSA with significant employer contributions
- Paid holidays and flexible PTO
- Annual learning and development budget
- The salary for the successful applicant will depend on job-related factors such as education, training, work experience, business needs, and market demands.
- Total compensation also includes variable pay in the form of an annual target bonus and other cash incentives, with a combined potential of up to 50% of base salary.
Company info
- We combine deep AI product and engineering expertise with NTT DATA's industry knowledge, enterprise relationships, and systems integration capabilities to deploy AI solutions for enterprise customers globally.
Equal opportunity
- Employer
- NTT DATA AIVista is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, ancestry, sex, gender identity or expression, sexual orientation, age, disability, genetic information, marital status, military or veteran status, reproductive health decisions, or any other characteristic protected under applicable federal, state, or local law.
- NTT DATA AIVista is an equal opportunity employer.
- We do not discriminate based on race, religion, color, national origin, ancestry, sex, gender identity or expression, sexual orientation, age, disability, genetic information, marital status, military or veteran status, reproductive health decisions, or any other characteristic protected under applicable federal, state, or local law.
This listing is sourced directly from NTT Data Aivista's careers page and normalized into a canonical job model.