Jobs at Applaudo

Build and maintain backend services and REST APIs on GCP, implement CSV/PDF exports, integrate SSO/RBAC, ensure reliable data access with BigQuery/Cloud SQL, write unit and integration tests, support defect resolution, and collaborate on API design and documentation within structured engineering processes.

Facilitate and coach multiple software teams to deliver value using Agile and scaled frameworks (SAFe). Lead ceremonies and PI events, manage dependencies and risks, track delivery metrics, remove impediments, promote AI tools adoption, and align Product, Engineering, and leadership to improve predictability and continuous improvement.

Lead AI product vision, strategy, and roadmap; prioritize initiatives, manage backlog, translate requirements into user stories, and drive adoption of LLMs, RAG, semantic search, and enterprise knowledge solutions while ensuring Responsible AI and governance.

Design and document cloud-native Node.js architectures on Azure, define backend/frontend patterns, integrations, and ADRs; guide development, DevOps, and data teams; present and defend technical roadmaps to stakeholders and executives.

Design, build, test, and maintain cloud-based ETL/ELT pipelines for geospatial and operational data. Implement spatial transformations and geospatial data models in BigQuery, integrate APIs and feeds, enforce data-quality controls, troubleshoot discrepancies, and produce clear technical documentation while collaborating across distributed engineering teams.

Lead end-to-end technical recruiting for software, data, cloud, and QA roles: develop long-term sourcing strategies, partner with hiring managers, design interview and assessment processes, coordinate interviews, mentor junior recruiters, and improve recruitment tools and operations to deliver timely, market-aligned hires and excellent candidate experience.

Design, govern, and evolve enterprise data architectures and ecosystems. Develop data models (star/snowflake), oversee metadata and governance, recommend cloud data platforms, provide architectural guidance, and collaborate with stakeholders to enable analytics, AI, and secure scalable data solutions.

Design, document, execute, and maintain functional, manual, regression, and end-to-end test cases. Validate user journeys and business processes, identify and track defects with clear reproduction steps, and perform project-specific on-site testing in El Salvador (including biometric validation). Manage assigned QA activities independently and collaborate with developers to resolve issues.

Support budgeting, forecasting, and financial reporting by maintaining financial models, preparing monthly and executive reports, managing invoicing and vendor payments, monitoring collections and profitability, and collaborating with Accounting to ensure accurate revenue recognition and reconciliations.

Design, build, and optimize ETL/ELT pipelines and data migrations. Transform, cleanse, and standardize data across platforms, ensure data quality and integrity, support scalable data models and analytics/AI integrations, and collaborate with teams to improve reliability and operational efficiency.

Lead multi-quarter roadmaps and prioritize features; own end-to-end product delivery (discovery, design handoff, development, UAT, releases); groom backlog with user stories and acceptance criteria; mediate Engineering, Design, and stakeholders; drive user research and usage reporting; use AI tools to accelerate delivery and prototyping.

Drive early-stage pipeline through high-volume digital outreach, inbound engagement, and structured qualification. Conduct discovery calls, validate technical fit, maintain HubSpot CRM hygiene, support proposals, collaborate with Solutions Architecture and Sales Operations, and ensure smooth handoffs to Account Executives while improving sales processes and reporting.

Lead and coordinate software delivery across multiple workstreams using stage-gate or milestone-based methodologies. Manage scope, dependencies, risks, change requests, and approvals; maintain governance and project documentation; prepare executive status reports; facilitate communication among engineering, product, delivery, and customer teams; and drive continuous improvement to protect timelines and meet customer expectations.

Lead AI product discovery, translate business needs into AI product specs, design and prototype AI Agents using Google ADK and LLMs, deploy and validate with Vertex AI Agent Engine, run iterative feedback cycles, design human-in-the-loop governance, create documentation, and drive stakeholder alignment and adoption.

Design and implement AI-powered testing agents and LLM-driven workflows to generate, execute, and validate automated test scenarios. Develop and maintain API automation with Playwright and mobile frameworks using WebDriverIO. Integrate AI-driven tests into CI/CD, document execution evidence, refine prompts and outputs, and collaborate with engineering teams to improve testing strategies and tooling.

Design, build, and maintain scalable TypeScript full-stack applications with a backend focus. Develop serverless AWS services (Lambda, API Gateway, DynamoDB) using AWS CDK, implement OpenAPI-based REST APIs with Zod validation, create modern React frontends, write unit and automated tests, participate in code reviews and Agile ceremonies, troubleshoot production issues, and ensure security and reliability.

Author and maintain full-stack features in a multi-tenant SaaS platform: React/TypeScript frontends (data-heavy UIs), Python/FastAPI or Node.js APIs, and PostgreSQL queries. Work inside existing architecture to implement secure, performant features, integrate AI-backed functionality, participate in Scrum, code review, and engage with senior stakeholders. This is a 6-month contract with possible extension.

Design, build, and evaluate ML and LLM-based matching systems for company/entity resolution. Develop embeddings, scoring, ranking, and classification models on messy, multilingual data. Define benchmarks, metrics, baselines, and run experiments with robust error analysis while considering inference cost, scalability, and production maintenance. Communicate results and recommendations to engineering and business stakeholders.

Design, implement, and maintain Azure tenant platforms and landing zones aligned with Microsoft CAF. Build and manage IaC using Terraform, optimize Terraform state and secrets, and operate CI/CD pipelines in Azure DevOps. Automate provisioning and scripting, enforce governance and policy, monitor performance/security/cost, and provide technical guidance and operational support to cross-functional teams.

Own, optimize, and stabilize production-scale data platforms: refactor schemas, improve Airflow pipelines, build and maintain dbt models, profile and tune Snowflake, implement data quality testing, and resolve production incidents end-to-end.