Lead AI Engineer

TL;DR

Lead AI Engineer (AI/ML): Building next-generation AI and ML systems including agent flywheels with self-improving feedback loops that evaluate, optimize, and evolve agent performance. Focus on designing production-grade ML models, data pipelines, evaluation frameworks, and hybrid systems blending LLMs, ML, and business logic for scalable agent workflows.

Hybrid, Mexico City

Company

Leading enterprise SaaS provider focused on CRM and cloud solutions.

What you will do

• Design and implement agent flywheels with feedback loops for self-improvement, including outcome tracking, evaluation, and iterative optimization.
• Build and deploy production ML models and AI agents integrating LLM reasoning, tool usage, and decisioning layers into workflows.
• Develop scalable data pipelines for training, evaluation, and inference, ensuring data quality and continuous retraining.
• Create evaluation frameworks, A/B experiments, and metrics monitoring to drive agent and model optimization.
• Design hybrid architectures combining deterministic logic, ML scoring, and LLM generation, scalable with growing complexity.
• Build Python services, APIs, and contribute to shared infrastructure for model serving and observability.

Requirements

• 6+ years in AI/ML engineering, applied data science, or related roles.
• Strong Python for production systems, ML model deployment, data pipelines (ETL/ELT), API/backend development.
• Experience with AI agents, LLM systems, agent traces, and ML lifecycle tooling.
• Expertise in data processing (Spark), orchestration (Airflow/Dagster), warehousing (Snowflake/BigQuery).
• Knowledge of supervised learning, evaluation methods, A/B testing, and hybrid ML/LLM/business logic systems.
• Production deployment skills with model serving, monitoring, and scalable code.

Nice to have

• Model-driven agent improvement systems, reinforcement learning, or bandits.
• Agent evaluation tools like LangSmith or Braintrust.
• Large-scale experimentation platforms.
• Enterprise SaaS or CRM domain experience.

Culture & Benefits

• High-impact role shipping systems that influence agent performance, efficiency, revenue, and customer experience.
• Collaboration with platform teams on shared infrastructure.
• Focus on robust, scalable systems with clear business metric improvements.