UJET

• Design and manage GCP project structure, networking, and core infrastructure • Own Kubernetes cluster infrastructure (provisioning, upgrades, scaling, reliability) • Define and maintain infrastructure-as-code (Terraform) standards and patterns • Improve system-level architecture for scalability, resilience, and performance • Build reusable infrastructure patterns that product teams can safely adopt • Reduce friction for developers while maintaining strong guardrails • Partner with engineering teams to improve how services are deployed and operated • Manage and evolve base observability systems (metrics, logging, tracing foundations) • Build and maintain infrastructure for secrets management, IAM, and security primitives • Ensure infrastructure is secure by default, not by exception • Improve infrastructure reliability and reduce systemic risk • Lead and contribute to incident response when infrastructure is involved • Identify and eliminate infrastructure-level failure modes and bottlenecks • Drive cloud cost visibility and optimization • Build systems and practices that balance performance, reliability, and cost • Partner with leadership to align infrastructure investment with business needs • Shape infrastructure strategy across teams and services • Drive adoption of standards and best practices across engineering • Identify systemic issues and lead cross-team improvements.

• Own and influence the architectural direction of the platform across frontend, backend, integrations, and supporting services. • Design scalable, maintainable, and resilient solutions that align with business objectives and technical strategy. • Evaluate architectural tradeoffs and make informed, decisive recommendations. • Establish and promote engineering standards, design patterns, and development best practices. • Drive technical consistency and quality across multiple teams and services. • Lead technical design reviews and provide guidance on complex engineering initiatives. • Contribute hands-on to the development of high-quality software across the full technology stack. • Design and implement solutions that prioritize performance, reliability, security, and maintainability. • Collaborate with engineers to solve complex technical challenges and unblock critical initiatives. • Review code and system designs to ensure adherence to engineering standards and architectural principles. • Champion continuous improvement of development processes, tooling, and operational excellence. • Lead investigation and resolution of complex production issues and system failures. • Demonstrate exceptional debugging and root cause analysis capabilities across distributed systems and application layers. • Identify systemic issues and implement long-term solutions that prevent recurrence. • Drive post-incident reviews and foster a culture of learning and operational excellence. • Serve as a mentor and technical coach for Senior Engineers and other technical leaders. • Help develop engineering talent through knowledge sharing, technical guidance, and constructive feedback. • Raise the technical capabilities of the organization by promoting best practices and engineering excellence. • Influence technical decision-making through strong communication, collaboration, and credibility. • Partner with Product Management, Engineering Leadership, and other stakeholders to align technical solutions with business needs. • Communicate complex technical concepts clearly to both technical and non-technical audiences. • Build consensus among teams while maintaining the ability to make and advocate for difficult technical decisions when necessary. • Drive alignment across multiple engineering teams on architecture, priorities, and execution strategies.

• 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 • Build user-facing experiences and internal interfaces using modern JavaScript/TypeScript when needed • 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

Role Description We’re looking for an AI Software Engineer to help build the next generation of UJET's AI products: Spiral and AXO. This is a high-impact role for someone who thrives in ambiguity, enjoys moving across the stack, and wants to turn cutting-edge model capabilities into real-world product experiences. - Work across backend systems, AI services, product features, APIs, and infrastructure. - Build agent workflows in Python, ship customer-facing features in TypeScript, improve evals and reliability, or design systems that process large-scale conversational data securely and efficiently. This role is ideal for an engineer who is deeply practical about AI: someone who uses AI-assisted development naturally, understands how to build with and around LLMs, and cares about reliability, performance, and user impact as much as model quality. We value curiosity highly. The best people in this role are excited to dig into messy problems, ask good questions, and iterate until the system is measurably better. Qualifications - 3-5 years of professional software engineering experience, with strong hands-on experience building production systems. - Strong experience as a generalist engineer who can move fluidly between backend systems, frontend, AI services, APIs, and product development. - Excellent programming skills in Python and TypeScript. - Experience shipping AI agents, LLM-powered applications, or other production AI systems, including prompt and tool orchestration, evaluation, and cost/reliability tradeoffs. - Strong product instincts and comfort working in ambiguous environments where the right solution is not obvious at the start. - Experience building and operating systems on AWS/GCP in production. - Comfort working with large, messy datasets and building pipelines that turn unstructured inputs into dependable product functionality. - Strong SQL and data systems fundamentals. - A bias toward ownership, speed, and pragmatic execution. - Experience building AI-native products from 0 to 1. - Familiarity with conversational data, support platforms, CRM/CCaaS integrations, or customer experience tooling. - Experience with observability, evaluation frameworks, and production reliability for AI systems. Requirements - Build and own product and platform capabilities across Spiral and AXO, from early prototypes to production systems. - Design and implement AI-powered workflows, agent capabilities, and backend services that are scalable, secure, and reliable. - Develop high-performance APIs, async workers, and application logic in Python and TypeScript. - Ship user-facing product features and internal tools that make advanced AI systems useful and intuitive for customers. - Architect and improve data ingestion, parsing, and analysis pipelines that transform raw customer interaction data into structured, actionable insights. - Partner across engineering, product, and design to translate ambiguous product ideas into robust technical systems. - Own infrastructure and deployment patterns on AWS/GCP, with a focus on reproducibility, observability, security, and cost efficiency. - Improve system quality through evaluation, monitoring, logging, alerting, and operational best practices. - Help define engineering standards, review code, and mentor teammates working on distributed systems and AI applications. Benefits - Medical, dental, vision, 401(k) plan, commuter benefits, and more.

• Lead efforts to improve system reliability, scalability, and performance across critical services • Define and implement SLIs/SLOs and error budgets, and use them to guide engineering priorities • Design and develop observability systems (metrics, logging, tracing, alerting) that produce actionable alerts and data with minimal noise • Lead complex incident response, acting as incident commander when needed • Conduct postmortems focused on systemic causes rather than individual fault, and ensure corrective actions from those reviews are completed. • Identify and eliminate toil through automation, tooling, and improved workflows • Partner with product and platform teams on architecture decisions, production readiness, and designing systems that recover from failure • Build reusable systems and “paved roads” that make it easier for teams to operate their services reliably • Mentor other engineers and raise the overall operational maturity of the organization

• Build and own product and platform capabilities across Spiral and AXO, from early prototypes to production systems. • Design and implement AI-powered workflows, agent capabilities, and backend services that are scalable, secure, and reliable. • Develop high-performance APIs, async workers, and application logic in Python and TypeScript. • Ship user-facing product features and internal tools that make advanced AI systems useful and intuitive for customers. • Architect and improve data ingestion, parsing, and analysis pipelines that transform raw customer interaction data into structured, actionable insights. • Partner across engineering, product, and design to translate ambiguous product ideas into robust technical systems. • Own infrastructure and deployment patterns on AWS/GCP, with a focus on reproducibility, observability, security, and cost efficiency. • Improve system quality through evaluation, monitoring, logging, alerting, and operational best practices. • Help define engineering standards, review code, and mentor teammates working on distributed systems and AI applications.

• Working closely with an assigned Technology Services Distributor to identify the in-market CX/AI-focused partners to drive mindshare, pipeline growth & UJET Sales. • Develop and build fiscal quarter and annual strategy. Report on, manage and execute on mutually agreed upon KPIs. • Initiate quarterly QBRs to measure success and trends within assigned TSD / Strategic partnerships. • Develop relationships internally and externally. Build and strengthen relationships with partner leadership and stakeholder business units throughout TSD or Partner organization • Aligning the regional sales organizations with relevant partners through targeted demand generation and alignment activities • Drive mindshare through regular communications and collaboration. Provide accurate and detailed weekly, monthly and quarterly forecast funnel of identified and proposed opportunities to meet or exceed quota requirements

• Lead and grow the Core Infrastructure team, setting vision, priorities, and execution for foundational cloud services. • Own the design, deployment, and operation of shared cloud primitives: GCP orgs & folders, networking, load balancers, compute, base images, Terraform frameworks, and upgrades. • Define and enforce best practices for scalability, security, observability, and maintainability across the cloud platform. • Partner with product and engineering teams to enable fast, safe, and reliable development and deployment workflows. • Drive continuous improvement in processes, automation, and infrastructure reliability. • Mentor and develop team members, fostering a culture of ownership, collaboration, and technical excellence.

• Build and evolve the data platform foundations that make it easy and safe for others to ship dbt work (project structure, environments, permissions, patterns, documentation) • Establish and maintain standards and guardrails for dbt development (testing strategy, source freshness, documentation, code review practices) • Improve the developer experience for data workflows, including CI/CD, automated checks, and repeatable deployment patterns • Partner with Analytics and Finance to define and deliver trusted metrics and dashboards in Looker • Build and maintain analytics-ready datasets that support self-serve reporting and experimentation • Develop and optimize BigQuery data models for analytics and product use cases • Implement ELT best practices in dbt, including testing, documentation, and versioning • Design, build, and maintain scalable data pipelines using Python and dbt • Ensure data quality, reliability, and observability for critical datasets and reporting • Optimize performance and cost across BigQuery and data pipelines • Integrate data workflows with backend services and APIs • Participate in infrastructure decisions related to data ingestion and platform evolution

• Identify and Drive Expansion: Act as the primary strategic advisor for assigned accounts, leveraging deep product knowledge to identify, qualify, and close expansion opportunities (upsell/cross-sell). • Commercial Success Planning: Develop and execute comprehensive Success Plans that align product adoption with the customer’s long-term business goals, specifically designed to drive account growth and seat expansion. • ROI as a Sales Tool: Quantify and present the ROI and cost-savings of the solution to justify contract renewals and provide the commercial rationale for increased investment. • Retention & Risk Mitigation: Proactively manage the customer lifecycle to ensure 100% retention; execute aggressive risk-mitigation plans for "at-risk" accounts to protect annual recurring revenue (ARR). • High-Impact Business Reviews: Orchestrate and lead Executive Business Reviews (EBRs) that move beyond tactical updates to focus on strategic value, future roadmap alignment, and commercial partnership opportunities • KPI Alignment for Renewal: Establish and improve baseline KPIs that matter most to the customer, using these metrics to prove the solution's indispensability during renewal cycles • Executive Relationship Management: Build high-level advocacy within customer organizations through persuasive storytelling and data-driven presentations that align UJET’s value proposition with the customer’s strategic vision. • Monetized Adoption: Guide customers to increase adoption of specific features and modules that correlate with higher customer lifetime value (LTV) and lower churn. • Strategic Best Practices: Educate customers on industry-specific best practices that encourage deeper integration of the solution into their tech stack, making the product "sticky." • Customer-Centric Feedback Loop: Collect and synthesize customer feedback for Product and Engineering teams to ensure the roadmap supports features that drive marketability and upsell potential. • Cross-Functional Sales Partnership: Collaborate regularly with Sales, Marketing, Product and Executive teams to lead initiatives that benefit the wider organization and improve the "land and expand" strategy. • Resolution for Retention: Manage and advocate for complex technical escalations, ensuring a resolution that protects the commercial relationship and respects internal processes. • Cadence & Priority Alignment: Maintain a consistent cadence with customers to ensure UJET remains their primary partner for achieving short-term wins and long-term strategic objectives.