About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engineering Manager AI based in Mexico.
Responsibilities
- 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 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.
- Ensure AWS infrastructure, CI/CD, observability, dashboards, tracing, and on-call practices meet strong reliability standards.
- Apply appropriate PCI-DSS and data-handling considerations.
- Translate product vision and business priorities into executable technical roadmaps.
- Partner closely with Product, Operations, and Modeling leadership.
- Represent the AI/ML engineering team's 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.
- Hands-on familiarity with modern AI/ML systems, including model training and serving, LLM-powered workflows, agents, RAG, orchestration.
- Practical experience with LLM-based systems in production.
- Strong technical understanding of backend systems, distributed architectures, APIs, and production engineering practices.
- Experience with Go, Python, gRPC, REST APIs, event streaming, and distributed systems.
- 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.
- Knowledge of LLM and agent technologies such as LangGraph, LangChain, RAG, vector databases, prompt engineering, and LLM evaluation.
- Familiarity with observability technologies including Prometheus, Grafana, OpenTelemetry.
- Payments, fintech, or experience in another regulated and latency-sensitive industry is a strong plus.
Conditions
- 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.