Sonatafy Technology - Mexico

Full-stack Engineer

• Design, develop, and maintain new application features while ensuring existing functionality remains robust and well-tested
• Write efficient and maintainable code with comprehensive test coverage, collaborating with QA engineers to test features and automate testing
• Co-deliver and validate integrated technology solutions with the client and partner technology team members
• Collaborate within an Agile Scrum team, engaging in sprint planning, daily standups, backlog refinement, and sprint reviews
• Develop a deep understanding of our customer's software and participate actively in code reviews and design discussions, providing constructive feedback and suggesting technology and process enhancements
• Partner with Product team members, DevOps engineers, and InfoSec professionals to align development efforts with business goals

Senior Fullstack Engineer

Machine Learning Engineer

• Analyze large datasets to surface trends, patterns, and actionable business insights.
• Build and maintain data models, transformations, and pipelines using SQL and dbt.
• Collaborate with stakeholders to define metrics, KPIs, and reporting requirements.
• Support data governance, ensuring data quality, integrity, and accessibility across the organization.
• Document processes, workflows, and analysis outcomes for cross-functional teams.
• Design, build, and evaluate supervised and unsupervised ML models (classification, regression, clustering, forecasting).
• Lead problem framing conversations with stakeholders to translate business questions into ML-ready problem statements.
• Conduct feature engineering, selection, and transformation to prepare data for model training.
• Validate and communicate model performance using appropriate evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).
• Support lightweight model deployment and monitoring, flagging performance drift and recommending retraining triggers.
• Contribute to experiment design and A/B testing frameworks where applicable.

Senior ML Engineer

Data Engineer

• Data Engineering: Design, build, and maintain scalable data pipelines and ETL workflows.
• Write advanced SQL queries and implement optimization techniques for performance.
• Leverage Microsoft Azure & Fabric, Spark, and Python to automate complex workflows.
• Lead engineering efforts on machine learning and artificial intelligence projects.
• Integration Development: Develop and maintain robust web APIs (SOAP, REST) to support seamless data integration across internal and external systems.
• Collaborate with external vendors to ensure the integrity and functionality of integrations.
• Operational Support: Monitor and troubleshoot data processes, ensuring high availability and minimal downtime.
• Proactively identify and resolve bottlenecks or inefficiencies in data pipelines and integrations.
• Collaboration: Manage and prioritize work using the ticketing system while maintaining regular communication in stand-ups and stakeholder meetings.
• Conduct code reviews to ensure adherence to best practices and high-quality deliverables.
• Contribute to technical documentation for processes, tools, and workflows.
• End User Support: Provide tier 3 support to end users of integrated systems such as reporting and accounting.
• Partner with business owners to identify areas for improvement and gather requirements.
• Leadership & Mentorship: Mentor other team members by sharing knowledge, conducting training sessions, and providing guidance on best practices.
• Take ownership of complex projects, ensuring timely delivery and alignment with business objectives.

Senior Data Engineer

AI Engineer

• Design, build, and operate AI agents that perform multi-step reasoning, decision-making, and task execution across enterprise systems.
• Develop agent-based solutions using LLMs, tools/function calling, memory, and orchestration frameworks to automate end-to-end business processes.
• Implement human-in-the-loop, approval, audit, and exception-handling patterns to ensure safe and reliable automation.
• Define and track KPIs for agent effectiveness (e.g., cycle-time reduction, automation rate, error rate, cost savings) and continuously optimize performance.
• Design and maintain AI-driven workflows that integrate with enterprise applications (CRM, ERP, ticketing, content management, collaboration platforms).
• Build and expose services and APIs that allow internal applications to invoke AI agents and automation capabilities.
• Integrate and govern third-party AI platforms and services where they accelerate delivery and reduce operational risk.
• Ensure reliability, observability, and cost controls across automated processes.
• Develop and deploy LLM-powered capabilities including tool-using agents, prompt strategies, embeddings, vector search, and retrieval-augmented generation (RAG) where appropriate.
• Evaluate model and agent behavior using quantitative metrics, structured test cases, and regression suites.
• Apply guardrails, validation, and monitoring to ensure responsible, predictable, and secure AI behavior in production.
• Operate AI agents and automation solutions in production, responding to incidents, failures, and unexpected behaviors.
• Partner with IT Operations and Security to ensure solutions meet availability, security, privacy, and compliance requirements.
• Participate in on-call or escalation rotations as required for critical AI-enabled systems.
• Partner with business stakeholders to identify high-impact automation opportunities and translate them into AI agent designs.
• Provide technical leadership, design guidance, and mentorship to engineers working on AI and automation initiatives.
• Contribute to architectural standards, best practices, and documentation for agent-based AI systems.

Senior AI Engineer

Business Intelligence Developer

• Design, build, and maintain reports, dashboards, and data visualizations
• Write optimized queries to support complex business analysis in reports and ad-hoc queries
• Ensure accuracy, reliability, and performance of all reports and analytics solutions
• Drive development of advanced analytics capabilities with machine learning and AI
• Act as primary point of contact for business users regarding reporting and data inquiries
• Conduct trainings and office hours to improve self-service analytics adoption and outcomes
• Gather and analyze business requirements, translating them into technical solutions
• Respond to user tickets and bug reports in a timely manner
• Assist in designing and optimizing data models for reporting and analytics purposes
• Work with Data Engineers to define and improve data processes that serve reporting needs
• Monitor and maintain the performance and availability of all reports and analytics solutions
• Troubleshoot and resolve reporting-related issues, ensuring minimal downtime for end users
• Identify opportunities for process automation and efficiency across the data environment
• Enforce data governance policy
• Manage and prioritize work in ticketing system
• Maintain regular communication in stand-ups and stakeholder meetings
• Participate in code reviews to ensure adherence to best practices and high-quality deliverables
• Mentor other team members by sharing knowledge and providing guidance on best practices
• Take ownership of complex projects, ensure timely delivery of solutions that meet requirements
• Advocate for adoption and usage of our tools and new technologies across the company.

Senior Business Intelligence Engineer

QA Engineer

• Collaborate with the engineering team to refine work requests in an agile development system
• Develop comprehensive test plans and test cases as part of project planning
• Provide accurate estimates of effort and duration of QA tasks
• Create and maintain automated tests to validate pipeline requirements
• Write and optimize SQL queries for automated validations
• Build regression suites for critical datasets and dashboards
• Create and maintain deterministic test datasets and “golden” expected results
• Assist with the verification and recreation of user-reported data issues
• File detailed and actionable defect reports
• Work collaboratively with engineers to troubleshoot defects
• Continuously improve QA processes, frameworks, and tools for data testing and validation
• Integrate test automation with deployment and workflow tracking systems
• Schedule and manage automated test runs, ensuring execution
• Implement data observability checks and alerting
• Collect, consolidate, and analyze test and monitoring results
• Define and develop key performance indicators (KPIs) for measuring test effectiveness
• Manage and prioritize work using the ticketing system
• Conduct code reviews of test code and SQL validation logic
• Partner with Data Engineering and BI stakeholders
• Contribute to technical documentation of processes, tools, workflows, and standards
• Mentor other team members by sharing knowledge, conducting training sessions, and providing guidance on best practices.

Senior Fullstack Engineer

Senior ML Engineer

Senior Data Engineer

Senior AI Engineer

Senior Business Intelligence Engineer

Senior Data QA Engineer