AI Engineering Manager

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Take charge of project delivery from start to finish, ensuring governance, effective stakeholder communication, and accountability for results.

• Develop and coach a top-performing AI engineering team.

• Set technical standards and promote a culture focused on quality and practicality.

• Manage proposals and new business ventures.

• Determine technical feasibility and convey risks and trade-offs to clients.

• Establish realistic expectations for AI systems and communicate their limitations.

• Carry out technical reviews and architectural evaluations.

• Oversee the design and implementation of production-ready RAG systems, agentic frameworks, and LLM-powered solutions.

• Direct advanced prompt engineering practices.

• Conduct feasibility studies across prompting, RAG, fine-tuning, and traditional ML approaches.

• Coach engineers on AI system architecture and production deployment.

• Create evaluation frameworks, metrics, datasets, experiments, and go/no-go criteria.

• Implement procedures for categorizing model failures.

• Define production reliability benchmarks for AI systems.

• Develop scalable inference infrastructure and CI/CD pipelines.

• Automate the MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, and retraining.

• Design APIs, microservices, and orchestration layers to optimize for latency, cost, and reliability.

• Guide infrastructure decisions to balance technical excellence with business efficiency.

⛳️ Requirements

• 7+ years of experience in building and deploying AI solutions in production settings.

• 2+ years of direct leadership or technical management experience.

• Proficient in Python at an expert level.

• Strong understanding of Git practices.

• Experience with ML/LLM versioning and deployment strategies.

• Solid experience with cloud platforms such as AWS, Azure, or GCP, with a preference for Azure.

• Knowledge of containerization and orchestration.

• Hands-on experience with RAG, including chunking, embeddings, retrieval, reranking, and evaluation.

• Proven experience in MLOps/LLMOps using tools like MLflow, Weights and Biases, or similar.

• Practical skills in evaluation design, including metrics, dataset curation, and structured experimentation.

• Familiarity with event-driven architectures, APIs, and microservices.

• Ability to communicate clearly with engineering teams and senior stakeholders.

• Strong instincts for hiring and team-building.

• Demonstrated mentoring experience.

• Advanced proficiency in English for communication with global teams and client leadership.

🏝️ Benefits

• Certifications in AWS, Databricks, and Snowflake.

• Access to AI learning paths.

• Customized study plans, courses, and additional certifications specific to the role.

• Access to Udemy Business.

• English language lessons.

• Opportunities for travel to industry conferences and client meetings.

• Career development plans and mentorship programs.

• Special rewards for birthdays, work anniversaries, and personal milestones.

• Company-provided equipment.

• Flexible working arrangements.

• Social security coverage (IMSS).

• Christmas bonus (Aguinaldo) in accordance with Mexican law.

• Vacation premium (Prima Vacacional).

• Remote work bonus.

• Paid leave as per Federal Labor Law (LFT).

• Additional benefits as mandated by Mexican labor regulations.