Data & AI Engineering Lead

EX Squared LATAM; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

EX Squared LATAM is a digital transformation company building an AI-powered CRM platform for investment professionals. We seek a Data & AI Engineering Lead to direct a unified Data Engineering and AI team, shaping architecture while remaining hands-on.

The role combines technical leadership with direct engineering contributions in a fast-paced product environment. The successful candidate will manage delivery, mentor engineers, and ensure data integrity and security across data-intensive

Qualifications

• 7–8 years of professional Software Engineering experience, including backend development, distributed systems, or data-intensive applications.
• 3 years of hands-on Data Engineering experience, including data pipelines, ETL/ELT processes, transformations, integrations, and data quality.
• 2–3 years of technical leadership experience as Engineering Lead/Technical Lead/Engineering Manager.
• Proven experience mentoring, performance feedback, delegation, workload management.
• Strong Python experience applied to backend development, data processing, or automation.
• 4+ years of SQL and relational databases experience, including data modeling and query optimization.
• Experience with software architecture and scalable backend services.
• Experience leading end-to-end engineering delivery and QA.
• Understanding of AI/ML concepts and collaboration with AI engineers.
• Experience with cloud platforms (AWS/Azure/GCP).
• Familiarity with Git, CI/CD pipelines, containerization, modern dev workflows.
• Ability to translate business needs into technical initiatives.
• Strong analytical thinking and problem-solving.
• Advanced English proficiency for leading technical discussions.

Responsibilities

• Lead the unified Data and AI Engineering team with ownership of priorities and delivery.
• Guide architecture decisions by reviewing designs and pull requests.
• Ensure data-intensive systems meet data integrity, security, and scalability standards.
• Identify and reduce technical debt, defects, and security vulnerabilities.
• Remain hands-on through code reviews and engineering contributions when needed.
• Mentor engineers, manage performance, and promote professional development.
• Coordinate with AI specialists to understand requirements and risks.
• Translate product priorities into clear technical workstreams and tickets.
• Own delivery effectiveness and implement preventive improvements.
• Communicate delivery status and technical risks proactively.

Skills

Python

SQL

Data pipelines

ETL/ELT

AI/ML concepts

Cloud platforms

AWS

Azure

Google Cloud

Git

CI/CD

Containerization

Backend architecture

API design

Engineering leadership

English proficiency (Advanced)

Tools

AWS

Azure

Google Cloud Platform

Git

CI/CD pipelines

Containerization

Job description

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.

• 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 integrations, and data-intensive applications.
• Experience leading end-to-end engineering delivery, including technical planning, backlog prioritization, task allocation, execution tracking, and quality assurance.
• Strong understanding of software engineering best practices, including code reviews, automated testing, secure development, and technical debt management.
• Practical understanding of AI/ML concepts and AI-powered applications, with the ability to collaborate effectively with specialized AI engineers.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with Git, CI/CD pipelines, containerization, and modern development workflows.
• Experience identifying and addressing risks related to reliability, security, data integrity, scalability, and performance.
• Ability to balance hands‑on technical work with architecture, people leadership, and delivery responsibilities.
• Experience collaborating with Product Management and cross-functional stakeholders to translate business needs into actionable technical initiatives.
• Strong analytical thinking, problem-solving, decision-making, and organizational skills.
• Advanced English proficiency, with the ability to lead technical discussions with U.S.-based stakeholders.
• Ability to work independently, manage changing priorities, and take ownership of engineering outcomes.

Technical Knowledge

• Data models, pipelines, transformations, integrations, validation, consistency, and data quality.
• Relational databases, SQL, data integrity, database performance, and secure handling of customer records.
• APIs, service-oriented systems, backend architecture, scalability, reliability, and maintainable implementation patterns.
• Pull-request reviews, automated testing, secure development, technical debt management, and defect prevention.
• Technical planning, requirement decomposition, estimation, prioritization, and delivery tracking.
• AI-enabled workflows, AI integrations, and coordination with AI/ML specialists.
• Incident escalation, technical risk communication, quality monitoring, and continuous process improvement.
• Hands‑on development experience with a modern backend or data engineering language.

Preferred Qualifications

• Experience working in a growth‑stage startup or scaling B2B SaaS company.
• Experience with CRM platforms, investment technology, private equity, financial services, or other data-intensive business applications.
• Experience leading cross-functional initiatives involving Data Engineering and AI/ML teams.
• Exposure to production AI-powered features, AI integrations, or applied machine-learning workflows.
• Experience integrating teams or establishing engineering processes during periods of organizational growth.
• Experience with Python-based backend ecosystems and modern cloud environments.
• Demonstrated success improving engineering quality, reducing production defects, strengthening security, or increasing team effectiveness.

This opportunity is available to candidates who are currently located and legally able to work remotely from an approved country in Latin America. Candidates must be able to maintain substantial overlap with U.S. Eastern Time business hours.