Engineering Manager AI

Team: IT

Location: Mexico

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Lead and grow a team of AI/ML, backend, and platform engineers, including hiring, performance management, coaching, retention, and career development.
• Coach engineers through technical designs, architecture decisions, code reviews, and complex engineering trade-offs.
• Establish and maintain high engineering standards across code quality, testing, CI/CD, and development practices.
• Own delivery planning for the team, including accurate costing, estimation, sequencing, prioritization, and accountability for commitments.
• Guide architecture for ML model lifecycle processes, including training, evaluation, monitoring, and retraining.
• Oversee LLM-powered workflows such as agent orchestration, RAG pipelines, vector database integrations, and related AI systems.
• Provide technical oversight for inference services supporting live payment routing, ensuring strict latency, reliability, and scalability requirements are met.
• Ensure AWS infrastructure, CI/CD, observability, dashboards, tracing, and on-call practices meet strong reliability and operational standards.
• Apply appropriate PCI-DSS and data-handling considerations to systems and services that interact with payment data.
• Translate product vision and business priorities into executable technical roadmaps with clear timelines, scope, and trade-offs.
• Partner closely with Product, Operations, and Modeling leadership to maintain alignment and create short feedback loops.
• Represent the AI/ML engineering teams progress, priorities, risks, and blockers to senior leadership.

Requirements

• 8+ years of professional software engineering experience, including 2–3+ years managing and leading engineering teams.
• Proven experience building and shipping backend and/or machine learning systems at scale.
• Experience hiring, developing, retaining, and managing engineers while balancing people development with delivery objectives.
• Hands-on familiarity with modern AI/ML systems, including model training and serving, LLM-powered workflows, agents, RAG, orchestration, or related technologies.
• Practical experience with LLM-based systems in production, particularly agents, RAG pipelines, or AI workflow orchestration.
• Strong technical understanding of backend systems, distributed architectures, APIs, and production engineering practices.
• Experience with technologies such as Go, Python, gRPC, REST APIs, event streaming, and distributed systems is valuable.
• Familiarity with AWS infrastructure and services, including ECS/EKS, Terraform, RDS/Aurora, and S3.
• Experience with AI/ML technologies such as PyTorch, TensorFlow, XGBoost, scikit-learn, MLflow, or Weights & Biases is beneficial.
• Knowledge of LLM and agent technologies such as LangGraph, LangChain, RAG, vector databases, prompt engineering, and LLM evaluation is valuable.
• Familiarity with observability technologies and practices, including Prometheus, Grafana, OpenTelemetry, structured logging, and on-call runbooks.
• Payments, fintech, or experience in another regulated and latency-sensitive industry is a strong plus, including familiarity with PCI-DSS, tokenization, or payment service provider integrations.
• Strong communication and stakeholder management skills, with the ability to communicate clearly with both technical and non-technical partners.
• Comfortable operating in a rapidly changing startup environment, with the ability to adapt scope, priorities, and communication while maintaining team trust.
• Strong growth mindset, self-awareness, and commitment to continuous improvement.

Benefits

• Vacation and additional paid time off.
• Remote work from anywhere.
• Financial support for health insurance, internet, and mobile phone expenses.
• Stock options.
• Access to a learning and development platform.
• Multidisciplinary, diverse, and dynamic team environment.
• Opportunities for professional growth and career development.
• Exposure to modern AI, ML, cloud, observability, and payments technologies.
• Opportunity to contribute to a high-impact payments platform serving a broad regional market.
• Startup environment characterized by agility, innovation, ownership, and continuous development.