Data & AI Engineering Lead

At EX Squared LATAM , we are a digital transformation company focused on developing innovative, high-impact technology solutions that create real business value. We work with leading clients across global, regional, and local markets, fostering a collaborative, inclusive, and innovation-driven culture where every team member’s ideas matter.

We are looking for a Data & AI Engineering Lead to support a U.S.-based B2B SaaS company developing an AI-powered CRM platform for investment professionals.

This position will lead a unified Data Engineering and AI team, providing technical direction, people leadership, delivery ownership, and operational structure. The ideal candidate is a hands-on engineering leader with strong experience in data-intensive systems, backend architecture, and managing engineering teams in a fast-paced product environment.

This is not a purely managerial role. The selected professional will remain actively involved in architecture, code reviews, troubleshooting, technical decisions, and direct engineering contributions when needed.

Position Details

• Employment Type: Full-time
• Location: 100% remote within Latin America
• Schedule: Significant overlap with U.S. Eastern Time business hours
• English Level: Advanced English proficiency required (B2+/C1)

Responsibilities

• Lead the technical execution of the unified Data and AI Engineering team, ensuring clear ownership of priorities, delivery commitments, quality, and results.
• Establish and advance the team’s technical direction by evaluating architecture options, reviewing designs and pull requests, and guiding complex implementation decisions.
• Ensure data-intensive systems meet high standards for data integrity, security, reliability, scalability, and maintainability.
• Identify and reduce technical debt, recurring defects, architectural risks, and potential security vulnerabilities.
• Remain hands-on through code reviews, troubleshooting, technical design discussions, and direct engineering contributions when appropriate.
• Lead, mentor, and support engineers by providing actionable feedback, managing performance, balancing workloads, and promoting professional development.
• Assess team capacity, identify overload risks, and redistribute work to support sustainable delivery.
• Translate product and business priorities into clear technical workstreams, user stories, actionable tickets, and ownership assignments.
• Assign engineering work based on each team member’s expertise, workload, task complexity, and business priority.
• Own delivery effectiveness and quality, investigating recurring QA findings and implementing preventive improvements.
• Coordinate closely with AI specialists to understand solution requirements, dependencies, and implementation risks.
• Support data engineering initiatives involving data processing, transformation, integration, consistency, and the secure handling of customer information.
• Collaborate with Product, Engineering leadership, and other stakeholders to clarify priorities and communicate technical trade-offs.
• Communicate delivery status, blockers, incidents, changes, and technical risks clearly and proactively.
• Recommend scalable process improvements while avoiding unnecessary bureaucracy.
• Promote a culture of accountability, critical thinking, collaboration, continuous learning, and customer-focused engineering.

Requirements

• At least 7–8 years of professional Software Engineering experience , including backend development, distributed systems, or data-intensive applications.
• At least 3 years of hands-on Data Engineering experience , including data pipelines, ETL/ELT processes, transformations, integrations, and data quality.
• At least 2–3 years of technical leadership experience as an Engineering Lead, Technical Lead, Engineering Manager, or similar role.
• Proven experience managing or leading engineers, including mentoring, performance feedback, delegation, workload management, and professional development.
• Strong programming experience, preferably with Python , applied to backend development, data processing, or automation.
• At least 4 years of experience with SQL and relational databases , including data modeling, database design, query optimization, and data integrity.
• Strong experience in software architecture and system design, particularly with scalable backend services, system integratio…