Enumerate

• Design and implement workflow automation and system integrations across enterprise SaaS platforms and internal systems. • Build cloud-native automation services and event-driven workflows using modern cloud platforms and APIs. • Develop integrations involving communication systems, ticketing platforms, CRM/workflow systems, and operational tools. • Implement secure OAuth-based authentication and enterprise access control models. • Build scalable orchestration services, queue-based processing, retry handling, and monitoring capabilities. • Develop AI-assisted operational workflows including classification, routing, summarization, extraction, and response assistance. • Design and maintain integration APIs, webhooks, and asynchronous processing pipelines. • Collaborate with operations, support, product, and engineering teams to identify automation opportunities and deliver workflow improvements. • Build observability, telemetry, audit logging, and operational reporting capabilities. • Ensure automation solutions meet security, compliance, governance, and reliability standards. • Leverage modern AI development tools (CursorAI, GitHub Copilot, ChatGPT, etc.) to improve engineering productivity and delivery speed. • Work closely with the technology team to ensure architectural and design alignment with Enumerate's technology strategy.

• Serve as the main point of contact for new clients during the onboarding and implementation process. • Guide clients through the activation, implementation and adoption of our Central, Engage and Payments software products, ensuring they achieve all milestones in a timely manner. • Collaborate with internal teams such as Sales, Implementation, Customer Success, and Product to ensure seamless transitions. • Provide training and guidance to clients to help them understand and adopt the platform efficiently. • Monitor the progress of each onboarding project, ensuring deadlines and client expectations are met. • Conduct regular check-ins with clients to troubleshoot issues, provide Tier 1 support, and track progress while customers are in the onboarding phase of their journey. • Document and maintain accurate onboarding records in the company’s systems. • Identify areas for improvement in the onboarding process and propose new methods to optimize efficiency and client satisfaction. • Participate in project scoping and resource allocation discussions to ensure proper execution of onboarding plans.

• Own outbound prospecting into Enumerate’s ICP: property management companies that manage HOA and COA communities • Build and maintain a qualified pipeline of meetings for the AE team through multi-channel outreach including phone, email, LinkedIn, and video • Qualify inbound leads and route them to AEs with the context and discovery that makes handoffs seamless • Conduct conversations that surface pain points, buying signals, deal context, and community count to set AEs up for success • Help build and refine outbound cadences, messaging, and targeting strategies alongside the VP of Sales and Head of Demand Generation • Test new approaches constantly: new channels, new messaging angles, new tools. What works stays, what doesn’t gets replaced • Provide frontline feedback on what prospects are saying, what objections come up, and where the pitch lands or falls flat • Document what works so the playbook gets sharper every week • Use modern sales tools (CRM, sequencing, prospecting platforms) to work smarter and faster • Lean into AI-powered tools for research, personalization, and outreach as part of your daily workflow • Bring ideas to the table on how to use technology to multiply your output and improve your results.

The Tech Lead is responsible for translating product ideas and data science capabilities into production-ready AI solutions. This role partners closely with Product Management and the Data Science Leader to rapidly design, prototype, and ship AI-driven features that deliver measurable business value. This is a highly hands-on technical leadership role focused on speed, pragmatism, and production quality, balancing experimentation with scalable engineering practices. This is a remote opportunity. We are seeking contractors located in LATAM who are comfortable working in an English-speaking professional environment. Key Responsibilities AI Solution Delivery & Architecture - Lead the technical design and implementation of AI-powered product features from concept through production. - Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration. - Make pragmatic decisions to accelerate delivery while maintaining system integrity. - Ensure AI solutions are secure, observable, scalable, and aligned with platform standards. Pod Leadership & Execution - Act as the technical lead for a cross-functional AI Pod. - Break down product requirements into executable technical workstreams and prototypes. - Guide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness. - Review code, architecture, and technical decisions to maintain quality and velocity. Product & Data Collaboration - Partner closely with Product Management to shape problem definitions, success metrics, and delivery plans. - Collaborate with the Data Science Leader to integrate models, analytics, and data assets into product workflows. - Translate data science outputs into consumable APIs, services, and product features. - Provide technical feedback on feasibility, scope, and tradeoffs during product discovery. Operationalization & Quality - Ensure features are production-grade, including monitoring, logging, and performance tracking. - Implement guardrails around AI usage, including reliability, latency, cost controls, and failure modes. - Support experimentation frameworks, A/B testing, and post-launch learning loops. - Drive responsible AI practices, including explainability, bias awareness, and data privacy considerations. Technical Standards & Enablement - Define and enforce lightweight engineering standards for AI-enabled systems. - Promote reuse of components, prompts, pipelines, and services across AI initiatives. - Mentor pod engineers on AI-adjacent system design and best practices. - Contribute to internal documentation and shared AI patterns/playbooks. Required Qualifications - BS or MS in Computer Science, Engineering, or related technical field. - 5+ years of software engineering experience, including leading complex systems. - Strong experience designing and building production APIs and backend services. - Proficiency in Python and at least one backend language (e.g., Java, Node.js, Go). - Experience with cloud-native architectures (AWS, GCP, or Azure). - Solid understanding of data pipelines, model serving, and system observability. - Ability to work closely with product teams in fast-moving, iterative environments. Preferred Qualifications - Experience working in AI-first or data-driven product teams. - Familiarity with modern LLM platforms, prompt engineering, and agent frameworks. - Experience operationalizing ML models (model serving, monitoring, versioning). - Exposure to experimentation platforms, feature flags, and A/B testing. - Experience in Agile or product-led development environments. Total monthly compensation: $3,300—$5,000 USD

• Investigate, diagnose, and resolve bugs in a vanilla PHP application. • Debug complex issues across application logic, database interactions, and integrations. • Deliver safe, well-tested fixes that minimize regression risk. • Take ownership of assigned features or components from development through release. • Write clear comments and documentation to support maintainability. • Collaborate with QA and Support to reproduce reported issues and validate fixes. • Analyze logs, error reports, and monitoring data to identify root causes. • Ensure fixes align with existing system behavior and user expectations. • Assist with minor performance improvements and reliability enhancements. • Participate actively in code reviews and technical discussions. • Apply agreed-upon standards for code quality, testing, and deployment. • Use AI-assisted development tools (such as CursorAI, GitHub Copilot, or similar) to accelerate development, testing, and documentation. • Contribute incremental improvements to shared utilities or internal tooling when beneficial.

• Lead annual budgeting, forecasting, and quarterly reforecast processes. • Develop and maintain financial models, forecasts, and KPI reporting, including SaaS metrics such as ARR, payments utilization, churn, retention, LTV/CAC, and gross margin. • Analyze financial results and provide variance analysis and actionable insights to support decision-making. • Prepare and deliver monthly and quarterly management reporting packages. • Monitor financial performance, including revenue, expenses, and cash flow. • Support cost management, resource allocation, and financial discipline across the organization. • Partner with department leaders on budget management and financial performance tracking. • Ensure consistency and integrity of financial data across systems and reporting. • Lead, coach, and develop the accounting team, including management of AR/AP, revenue, and senior accounting functions. • Oversee day-to-day accounting operations and the monthly, quarterly, and annual close processes to ensure timely, accurate reporting. • Ensure financial statements are compliant with GAAP and internal policies, including oversight of technical accounting matters and complex transactions. • Establish, maintain, and enforce accounting policies, procedures, and internal controls to support consistency, accuracy, and audit readiness. • Oversee revenue operations (order-to-cash), tax compliance, and cash management, including forecasting and liquidity planning. • Manage external relationships, including auditors, banking partners, and advisors, ensuring successful audits and compliance with debt and regulatory requirements. • Drive improvements in financial reporting, forecasting accuracy, and close efficiency. • Build and scale financial processes and controls to support company growth.

• Lead the technical design and implementation of AI-powered product features from concept through production. • Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration. • Make pragmatic decisions to accelerate delivery while maintaining system integrity. • Ensure AI solutions are secure, observable, scalable, and aligned with platform standards. • Act as the technical lead for a cross-functional AI Pod. • Break down product requirements into executable technical workstreams and prototypes. • Guide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness. • Review code, architecture, and technical decisions to maintain quality and velocity. • Partner closely with Product Management to shape problem definitions, success metrics, and delivery plans. • Collaborate with the Data Science Leader to integrate models, analytics, and data assets into product workflows.

• Design and implement user-facing AI features across frontend and backend systems. • Build and evolve APIs and services that integrate AI models, data pipelines, and product workflows. • Translate product requirements and UX designs into high-quality, maintainable code. • Rapidly prototype and iterate on AI-driven experiences based on user feedback and experimentation results. • Implement intuitive user interfaces that expose AI capabilities clearly and responsibly. • Collaborate with Product and Design to shape AI interactions, prompts, and workflows. • Develop backend services that orchestrate AI calls, business logic, and data access.

• Lead the technical design and implementation of AI-powered product features from concept through production. • Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration. • Make pragmatic decisions to accelerate delivery while maintaining system integrity. • Ensure AI solutions are secure, observable, scalable, and aligned with platform standards. • Act as the technical lead for a cross-functional AI Pod. • Break down product requirements into executable technical workstreams and prototypes. • Guide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness. • Review code, architecture, and technical decisions to maintain quality and velocity.

• Design and implement user-facing AI features across frontend and backend systems. • Build and evolve APIs and services that integrate AI models, data pipelines, and product workflows. • Translate product requirements and UX designs into high-quality, maintainable code. • Rapidly prototype and iterate on AI-driven experiences based on user feedback and experimentation results. • Implement intuitive user interfaces that expose AI capabilities clearly and responsibly. • Collaborate with Product and Design to shape AI interactions, prompts, and workflows. • Handle edge cases, fallbacks, and user feedback when AI outputs are uncertain or degraded. • Ensure UI performance, accessibility, and responsiveness. • Develop backend services that orchestrate AI calls, business logic, and data access. • Integrate with internal APIs, data services, and third-party AI platforms. • Implement secure, scalable request handling, including latency and cost considerations for AI usage. • Support feature flags, configuration, and experimentation frameworks. • Write automated tests across frontend and backend components. • Implement logging, monitoring, and basic performance tracking for AI-enabled features. • Participate in code reviews and adhere to team engineering standards. • Help diagnose and resolve production issues related to AI behavior, data, or integrations. • Work closely with the AI Pod Tech Lead to execute technical designs and standards. • Partner with data scientists and ML engineers to integrate models into product features. • Contribute ideas for improving AI usability, reliability, and developer productivity. • Share learnings and patterns across the AI Pod.