Principal Experience Engineer

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Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. What does this mean to you? For starters, it means joining a company focused on delivering outstanding innovation and support that helps customers increase revenue, lower costs and reduce risk. In fact, Precisely powers better decisions for more than 12,000 global organizations, including 95 of the Fortune 100. Precisely's 2500 employees are unified by four company core values that are central to who we are and how we operate: Openness, Determination, Individuality, and Collaboration. We are committed to career development for our employees and offer opportunities for growth, learning and building community. With a "work from anywhere" culture, we celebrate diversity in a distributed environment with a presence in 30 countries as well as 20 offices in over 5 continents. Learn more about why it's an exciting time to join Precisely!

Precisely is an AI-first organization. All employees are expected to demonstrate proficiency in applying AI tools to accelerate their work, improve output quality, and eliminate low-value tasks. Candidates should be comfortable using generative AI tools (e.g., Microsoft Copilot, ChatGPT) in their day-to-day workflows, able to evaluate AI-generated outputs critically, and open to continuously adopting new AI capabilities as they emerge.

• Define, build, and own the AI SDLC system for Experience Engineering — the agentic workflows, tooling, and guardrails our engineers rely on to ship
• Stay ahead of the industry on agentic SDLC best practices and bring them into our system, continuously raising the bar for how we build
• Maintain and evolve the system so it keeps working as models, tools, and team needs change — this is a living platform, not a one-time rollout
• Enable engineers across teams to get real leverage from AI — through patterns, examples, and hands-on support, not just documentation
• Partner with UX, UI, and QA Principal Architects to translate their direction into clear patterns and practices teams can follow
• Work shoulder-to-shoulder with teams to guide implementation, support hard decisions, and unblock complex work
• Reinforce quality ownership inside teams so testing and validation are part of everyday delivery, not a final gate
• Spot gaps between standards and reality, and close them with the teams doing the work
• Mentor engineers across the org and raise the overall standard of craft and delivery
• Use delivery metrics, quality signals, and direct feedback to drive continuous improvement

• Education: Bachelor’s degree in Computer Science, Design, or a related field; equivalent work experience is accepted in place of a degree
• Experience: 8+ years of professional experience across frontend engineering, experience design, and quality, including work across multiple teams
• Engineering skills: Demonstrated ability to build and guide development of production-ready interfaces using modern frontend frameworks (e.g. React, Vue, Angular, or similar)
• Quality skills: Strong experience with automated testing approaches and maintaining quality within CI/CD pipelines
• UX skills: Strong understanding of user experience and the ability to guide teams toward consistent, usable outcomes
• Demonstrated experience using AI-assisted development tools in a professional setting and guiding others in their use
• Comfortable using generative AI tools (e.g. Microsoft Copilot, GitHub Copilot, ChatGPT) to assist with code generation, test writing, and experience design
• Able to evaluate AI-generated outputs critically, including reviewing code, tests, and interactions for correctness, accessibility, and maintainability
• Open to continuously adopting new AI capabilities as they emerge in the engineering and design workflow.
• Preferred Skills:
  • Experience working across multiple teams or product areas
  • Familiarity with shared patterns, design systems, or component libraries
  • Experience mentoring engineers beyond a single team
  • Exposure to observability tools (LogRocket, Heap, Datadog, Sentry, etc.)
  • Exposure to backend systems or APIs to support collaboration on integration and testing

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