AI Engineer Senior
Requirements
- Minimum 4 years of experience in software engineering, including at least 1 year working with Large Language Models (LLMs), AI integrations, or agentic AI solutions.
- Strong programming skills in Python; experience with TypeScript and/or Go is an advantage.
- Proven experience developing and maintaining production-grade backend services and APIs (REST, gRPC).
- Hands-on experience integrating LLM platforms such as OpenAI, Anthropic, Google Gemini, or open-source models into business applications.
- Knowledge of structured outputs, tool/function calling, Model Context Protocol (MCP), and AI gateway implementations.
- Experience with agentic AI and orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or Semantic Kernel.
- Solid understanding of Retrieval-Augmented Generation (RAG) architectures, including chunking strategies, embeddings, vector databases (Pinecone, Weaviate, pgvector), and retrieval methodologies.
- Experience working with cloud-native technologies, including AWS and/or GCP, Kubernetes, Terraform, event-driven architectures, and messaging platforms such as Kafka.
- Familiarity with LLM evaluation, monitoring, and observability tools such as LangSmith, Weights & Biases, or custom evaluation frameworks.
- Experience managing and supporting production environments, including monitoring, incident response, platform upgrades, and operational support.
- Ability to work effectively in fast-paced, ambiguous environments while delivering iterative solutions and ensuring end-to-end service reliability.
- Excellent written and verbal communication skills with the ability to explain technical concepts and trade-offs to non-technical stakeholders.
Preferred Qualifications
- Experience with enterprise AI platforms such as Glean, Anthropic Claude, OpenAI, Gemini Enterprise, or Claude Code.
- Experience building agentic automation solutions for business operations and enterprise workflows.
- Knowledge of vendor management, platform lifecycle management, and technology roadmap alignment.
- Contributions to open-source AI/ML projects.
- Experience with model fine-tuning, inference optimization, and AI performance tuning.
Activities to Perform
- Design, develop, deploy, and maintain agentic AI solutions that support and optimize business operations across multiple organizational functions.
- Build and enhance Enterprise AI architecture and infrastructure, including agent orchestration frameworks, tool integrations, RAG pipelines, and LLM inference services.
- Lead the full AI solution lifecycle, from proof of concept and prototyping through production deployment and ongoing optimization.
- Monitor, maintain, and improve AI systems running in production to ensure reliability, performance, and availability.
- Manage platform updates, upgrades, and deployments while ensuring business continuity and operational excellence.
- Collaborate with AI technology vendors and platform providers (e.g., Glean, OpenAI, Anthropic, Gemini Enterprise) to implement new features and maintain alignment with product roadmaps.
- Implement observability, evaluation, governance, and safety controls to ensure responsible and reliable AI system operation.
- Participate in architecture and design reviews, evaluating trade-offs related to scalability, cost, autonomy, security, and safety.
- Partner with cross-functional teams to identify business opportunities, develop AI-driven solutions, and deliver end-to-end implementations.
- Evaluate emerging AI models, frameworks, and agentic patterns to continuously improve enterprise AI capabilities.
- Own the operational health, reliability, and performance of deployed AI services and infrastructure.
- Troubleshoot incidents, optimize system performance, and ensure adherence to enterprise standards and best practices.
Location: Mexico / Hybrid
Language: English Advanced
