AI Experience Engineer in New York at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Experience Engineer based in the United States.
This is a full-stack engineering role focused on building the human-facing layer of AI-powered and agentic systems.
You’ll turn concepts and prototypes into polished, production-quality experiences that make sophisticated AI capabilities intuitive, trustworthy, and useful.
The role spans backend services, APIs, data integration, frontend engineering, design systems, and AI-specific interaction patterns.
A major focus will be creating observability interfaces that allow people to inspect agent behavior, understand outputs, identify anomalies, and intervene when necessary.
You’ll help establish reusable patterns for AI assistants, copilots, real-time intelligence, and human-on-the-loop workflows across the organization.
Your work will be highly visible to engineering leaders, executives, and potentially external customers, making product quality and usability essential.
You’ll operate within an innovation-focused environment where experimentation, accessibility, thoughtful design, and modern AI engineering come together.
- Own the full-stack design and engineering quality of AI pilots and prototypes, taking concepts from briefs or wireframes through backend services, APIs, data integrations, and polished production-quality interfaces.
- Build intuitive, accessible, and visually consistent experiences that make complex AI capabilities immediately understandable to technical and non-technical stakeholders.
- Design and implement human-on-the-loop interaction patterns that allow users to inspect agent traces, review outputs, adjust parameters, identify anomalies, and intervene when appropriate without becoming bottlenecks in every AI workflow.
- Develop and maintain a shared design system and component library featuring AI-specific patterns such as streaming outputs, agent status indicators, progress states, trace inspection views, confidence surfaces, and human-review interfaces.
- Establish UX and interaction standards for AI assistants and copilots, including contextual assistance, real-time knowledge retrieval, AI-generated content, and role-specific intelligence dashboards.
- Conduct lightweight user research and usability testing with internal stakeholders and business partners, using feedback early enough to influence product direction and functionality.
- Collaborate with AI engineering partners to create evaluation interfaces and observability dashboards that make model behavior, agent traces, and system performance understandable to human reviewers.
- Champion WCAG accessibility standards, frontend performance, and high-quality engineering practices across innovation deliverables.
- Apply established brand and design standards to customer-facing and externally visible experiences.
- Contribute to frontend technology evaluations and emerging technology assessments, helping define technical direction for AI interaction patterns.
- Create and document reusable architectural and interaction patterns so successful AI experiences can be adopted by broader engineering teams and carried into production.
- Establish strong foundations early, including auditing existing design systems, shipping initial agent interaction components, building observability interfaces, and documenting design-system foundations for production teams.
- Strong full-stack engineering capabilities with significant frontend depth, including the ability to build backend services, integrate data sources, and deliver polished interfaces within the same development cycle.
- Demonstrated production experience building AI-powered systems, particularly applications involving streaming output, agent interactions, human-review workflows, trace inspection, or similar AI interfaces.
- Understanding of the non-deterministic nature of LLM-powered systems and the importance of designing for continuous inspection, observability, and human intervention.
- Strong experience with React or an equivalent modern frontend framework and contemporary design-system practices.
- Ability to move fluidly between UX design and implementation, including working with tools such as Figma and translating interaction concepts directly into production code.
- Experience designing interfaces for complex technical information while maintaining clarity and usability for non-technical audiences.
- Strong product intuition and a user-centered mindset, with the ability to determine what users actually need from an AI system before deciding how information should be presented.
- Experience with agent observability platforms such as Langfuse, LangSmith, Phoenix, Arize, or equivalent solutions is highly valued.
- Knowledge of data visualization, WCAG accessibility standards, and performance engineering is advantageous.
- Familiarity with LLM evaluation frameworks, eval harnesses, or LLM-as-judge approaches is a plus.
- Strong communication and collaboration skills, with the ability to work effectively across engineering, product, design, and business teams.
- Comfortable operating in an innovation environment where requirements evolve quickly and prototypes must balance experimentation with production-quality standards.
- Ability to take ownership of highly visible work, challenge assumptions constructively, and maintain a high bar for quality and usability.
- Starting salary: $130,000–$160,000 USD per year for US-based employees.
- For Canadian employees, a starting salary range of $115,000–$130,000 CAD per year.
- Compensation is determined based on relevant skills, education, qualifications, experience, performance, organizational needs, and geographic location.
- Remote work opportunities across the United States, with the broader role also supporting Canada, Europe, and Australia.
- Opportunity to work on cutting-edge AI assistants, copilots, agentic systems, and AI observability experiences.
- High-visibility projects presented to engineering leadership, executives, and potentially external customers.
- Opportunity to shape reusable AI interaction patterns and design-system foundations that can influence broader production engineering.
- Collaborative, innovation-focused environment emphasizing customer success, data-driven decision-making, trust, and continuous improvement.
- Inclusive workplace committed to equal opportunity, diverse perspectives, and belonging.
- Opportunities to work at the intersection of AI engineering, product design, frontend development, and emerging technology.