Role Description We are hiring a Software Engineer dedicated to our Shared Services operation. This is a ticket-driven role focused on rapidly solving real problems for the people who run our service operation every day. Your customers are internal: our agents in Manila, our Ops Leads and Team Leads, our Customer Success team, and our enterprise clients when they escalate technical issues. Every day, these groups file tickets describing things that are broken, slow, missing, or could be automated. Your job is to work through that queue, ship fixes, and build the tooling that compounds over time. This is not a roadmap-driven engineering role. You are not waiting for a PM to scope work. You are reading tickets, asking the right clarifying questions, prioritizing what matters, and shipping working code fast. You report into Engineering and partner directly with the Head of Operations and the Head of Shared Services Operations. What You Will Do Every Day - Triage incoming tickets from agents, Team Leads, Customer Success, and clients - Diagnose the underlying problem (often it is not what the ticket says) - Ship fixes, automations, and small tools that solve the immediate need - Identify patterns across tickets and build durable solutions that prevent the same ticket from coming back - Pair with operations users to validate that your fix actually worked - Maintain and improve the internal tools you build over time What You Will Build - An anomaly detector that flags AI replies violating OTA platform rules (Airbnb, VRBO ToS) before they reach the guest - A daily QA sampling tool that scores AI and agent responses and routes failures back into the knowledge base - A scheduling system that matches agent shifts to guest volume curves by hour and channel - A real-time operational dashboard pulling from Tailwind, Aircall, and HubSpot - Integrations between internal tools that today are connected by manual data exports - One-off scripts that solve a specific client or agent ticket and live as long as they need to - AI workflows that automate repetitive operational tasks (escalation routing, KB gap detection, client reporting) Some of what you ship will be polished products that live for years. Some will be quick scripts that solve one ticket and never run again. Both matter. What This Role Is Not - Not a customer-facing platform engineering role. You are not shipping product code to clients - Not a back-office IT role. You are building real software with real users - Not a project manager wrapped in an engineer title. You write code daily - Not a role where you wait for tickets to be perfectly scoped before you start. You scope them yourself Qualifications - 4+ years of software engineering experience, with at least 2 years shipping production code - Direct experience building internal tools, automations, or operational systems - Comfort working from a ticket queue (support engineering, forward-deployed engineering, or internal tooling background is ideal) - Product mindset: comfortable talking directly to non-technical users, scoping problems, and prioritizing tradeoffs - Track record of shipping fast in environments without dedicated PMs or designers - Experience working asynchronously with distributed teams Required Technical Skills - Strong fluency in Python and/or TypeScript - Experience with at least one workflow automation platform (n8n, Zapier, Make, Temporal, or similar) - Comfortable with agentic coding tools (Claude Code, Cursor, Replit Agent) - Database fluency (PostgreSQL preferred), able to write your own queries and design schemas - API integration experience (REST, webhooks, third-party SaaS APIs) - Prompt engineering experience with production AI systems (OpenAI, Anthropic, or similar) Strongly Preferred - Experience as a forward-deployed engineer or solutions engineer at a B2B SaaS company - Background in contact center, customer support, or service operations tooling - Short-term rental, hospitality, or property management domain knowledge - Experience integrating with Guesty, Hostaway, OwnerRez, Aircall, or HubSpot APIs - Track record of deploying AI agents in production (not just prototypes) How You Will Work - Embedded directly with Shared Services daily - Ticket queue is your primary input (Slack, ClickUp, email, escalations from CS) - Weekly syncs with Head of Operations and Head of Shared Services Operations to align on priorities - Async collaboration with the broader Engineering team - You own scoping, building, testing, and deployment of your work - We expect 4 hours of overlap with Miami time (Eastern Time) daily Location Remote, based in Europe or South America.

Role Description As a Lead Software Development Engineer in Test (SDET) at Point, you will be a technical leader within the Quality Engineering organization, driving the design, scalability, reliability, and maintainability of our quality engineering solutions across multiple product areas. You will partner closely with Engineering, Product, and Design leaders to embed quality into every stage of software development—from architecture and implementation to deployment and production monitoring. This is a hands-on individual contributor role focused on building scalable automation frameworks, improving developer productivity, and driving modern quality engineering practices. You will lead cross-team quality initiatives, mentor junior engineers, and leverage AI-powered testing solutions to enhance testing, reduce production risk, and help engineering teams deliver high-quality software with confidence. Your Responsibilities - Design, build, and evolve scalable automation frameworks for UI, API, backend services, and end-to-end testing. - Drive adoption of modern testing practices, including API, integration, component, contract, and risk-based testing, to reduce test execution time and accelerate engineering feedback cycles. - Build reusable automation libraries, tooling, and workflows that improve developer productivity and automation reliability. - Partner with Engineering, Product, and Design teams to improve application testability, reliability, and overall product quality. - Integrate automated testing into CI/CD pipelines and continuously improve test execution speed, stability, and coverage. - Define, track and analyze quality metrics, automation health, defect trends, and production issues to identify opportunities for improvement. - Leverage AI-powered testing solutions to improve test generation, maintenance, prioritization, and engineering efficiency. - Lead cross-team quality initiatives, providing technical guidance and promoting quality engineering best practices. - Participate in design and code reviews, providing guidance to improve application quality, testability, and maintainability. - Mentor and coach Quality Engineers and SDETs through technical guidance, code reviews, and automation best practices. - Collaborate with engineering teams throughout the software development lifecycle to ensure high-quality, reliable product releases. Qualifications - 8+ years of experience in Software Quality Engineering, with extensive hands-on experience in test automation. - Expert proficiency in JavaScript/TypeScript; experience with additional languages (e.g., Python, Ruby/Rails) is a plus. - Deep expertise with modern automation frameworks (e.g., Playwright, Selenium, Cypress) across UI, API, and backend testing. - Strong understanding of software architecture, distributed systems, CI/CD pipelines, and modern software development practices. - Experience designing and evolving scalable automation frameworks and reusable testing solutions. - Hands-on experience leveraging AI/LLM-powered tools to improve test generation, automation maintenance, engineering productivity, or developer workflows. - Experience with cloud environments and modern developer tools, including GitHub Actions. - Strong knowledge of relational databases and the ability to write efficient SQL queries. - Excellent analytical, debugging, and problem-solving skills. - Proven ability to mentor engineers, drive technical initiatives, and influence engineering best practices across teams. - Excellent communication and collaboration skills, with the ability to partner effectively across Engineering, Product, and Design. Nice to Have - Experience building internal developer platforms or engineering productivity tools. - Experience with contract testing, component testing, performance testing, and observability platforms. - Experience testing AI-enabled applications or evaluating LLM-based systems. - Contributions to open-source testing tools, technical blogs, or conference presentations. - Experience working in high-growth SaaS or fintech environments. Compensation Compensation at Point will be determined by skills, experience, and geographic location. CAD 133,676 - 147,748. This does not include any other potential components of the compensation package, including equity, benefits, and perks outlined above. Equal Opportunity Employer Point is proud to be an equal-opportunity employer. We provide employment opportunities regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. Each individual at Point brings their own perspectives, work experiences, lifestyles, and cultures with them, and we believe that a more diverse team creates more innovative products, provides better services to customers, and helps us all grow and learn.

• Build the tools and infrastructure that make every engineer in the vertical faster, sharper, and more capable • Design and build AI harness and scaffolding systems that operationalize AI coding tools across Servicing Digital's engineering workflows • Architect and implement context engineering infrastructure • Build workflow automation that integrates AI assistance into CI/CD pipelines, code review, testing, and developer feedback loops • Develop reusable tooling, templates, and frameworks that teams can adopt without requiring deep AI expertise • Instrument and evaluate AI workflow effectiveness • Work directly with engineers across Servicing Digital to understand real workflow friction

• Define vision and lead architecture for major systems and platforms, ensuring scalability and future readiness. • Guide technology adoption, focusing on large-scale Web & API architectures. • Build and maintain enterprise developer tools, robust CI/CD practices, and platform engineering standards. • Integrate and advocate use of AI-enabled coding/automation tools throughout the SDLC. • Mentor engineers and technical leaders, strengthening technical excellence across the company. • Influence business/product direction through deep technical expertise and cross-functional collaboration. • Act as thought leader via presentations, documentation, open source, or technical communities.