Data-Focused Full Stack Engineer Remote

UJET leads the way in AI-powered contact center innovation, delivering a future-proof, cloud platform that redefines the customer experience with cutting‑edge AI, true multimodality, and a mobile‑first approach. We infuse AI across every aspect of your customer journey and contact center operations, to drive automation and efficiency. UJET's AI solutions empower agents, optimize customer journeys, and transform contact center operations for elevated experiences and actionable insights.

Built on a cloud‑native architecture with a unique CRM‑first approach, UJET ensures unmatched security, scalability, and prioritized data insights (without storing PII). Designed for effortless use, UJET partners with businesses to deliver exceptional interactions, smarter decision‑making, and accelerated growth in the AI‑driven world.

You’ll join UJET’s Data and AI engineering organization, working at the intersection of full‑stack product engineering, data systems, and AI‑enabled customer experience. Our teams build and support the data platform, analytics foundations, AI integrations, virtual agent capabilities, agent assist experiences, and conversation intelligence systems that power UJET’s next generation of customer experience products.

This is a great role for an engineer who enjoys moving across the stack, learning quickly, and turning ambiguous product and data problems into reliable, production‑ready systems.

We’re looking for a Data‑Focused Full Stack Engineer to help build software and data systems that make AI‑powered customer experience products possible.

In this role, you’ll work across backend services, frontend product surfaces, data pipelines, analytics workflows, and AI system integrations. You’ll help transform customer interaction data into useful product experiences, operational insights, and automation capabilities. You should be comfortable writing production software, working with data, collaborating across teams, and learning new technologies as the problem demands.

Location: This role is US‑based. We have a preference for someone who lives in Maine, while remaining open to strong candidates elsewhere in the United States.

• Build and maintain full‑stack product features that use data and AI to improve customer, agent, supervisor, and administrator experiences
• Develop backend services, APIs, workflows, and integrations that connect product systems with data and AI capabilities
• Work with customer interaction data, conversation data, analytics models, and operational datasets to support AI‑powered features
• Partner with AI, Data Platform, Product, QA, and other engineering teams to design and deliver reliable customer‑facing systems
• Contribute to data pipelines, data models, and internal tools that make product and operational data easier to use
• Write maintainable, well‑tested code and participate in design reviews, code reviews, debugging, and production support
• Take ownership of ambiguous problems, break them down clearly, and drive them through delivery
• Learn new parts of the stack as needed and help raise the engineering quality bar for the team

• At least 3 years of professional software engineering experience
• Strong production experience with Python
• Experience building full‑stack applications, backend services, APIs, or data‑driven product features
• Experience working with data systems, data pipelines, analytics workflows, or data‑intensive applications
• Interest in or experience with building systems that support AI, machine learning, LLMs, virtual agents, agent assist, conversation intelligence, or automation
• Strong software engineering fundamentals, including testing, version control, code review, debugging, and maintainable system design
• Ability to work across multiple layers of a technical stack and learn unfamiliar technologies quickly
• Evidence of self‑motivated work, strong ownership, and the ability to make progress in ambiguous situations
• Clear written and verbal communication skills, especially in a distributed engineering environment
• Experience with cloud platforms

• Experience with Google Cloud Platform
• Experience with event‑driven…