Consultant AI Engineer

Location: Mexico; Work model: Remote

Company

Enterprise technology services work focused on production Generative AI and Agentic AI solutions.

What you will do

• Design, build, and harden production-grade Generative AI and Agentic AI solutions for enterprise use cases.
• Develop LLM-powered multiagent pipelines with RAG orchestration, tool integration, evaluation, deployment, and production pilots.
• Implement ReAct tool-use loops, supervisor-based and DAG orchestration, state management, selective reexecution, and human-in-the-loop approval gates.
• Integrate AI agents with enterprise systems through MCP, function calling, REST APIs, issue trackers, source control, and test management platforms.
• Build scalable RAG and hybrid retrieval solutions over proprietary enterprise data.
• Mentor and upskill internal engineering teams while supporting production delivery.

Requirements

• At least 5 years of software engineering experience, including at least 2 years focused on AI/ML, LLM applications, or agentic systems.
• Production experience with Agentic AI and multiagent frameworks such as AWS Strands SDK, LangGraph, CrewAI, or Claude Agent SDK.
• Hands-on experience with Amazon Bedrock and the AWS Generative AI stack, including foundation models, Knowledge Bases, Agents, S3, Lambda, IAM, ECS/EKS, or SageMaker.
• Strong Python engineering skills, including JSON schema design, schema validation, idempotency, error handling, transaction safety, and Git-based workflows.
• Experience with RAG, vector databases such as OpenSearch, embeddings, semantic and hierarchical chunking, metadata and taxonomy design, hybrid retrieval, reranking, and retrieval-failure verification.
• Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related technical discipline, or equivalent professional experience.

Nice to have

• Experience with Docker, Kubernetes, Terraform, or CloudFormation.
• Generative AI, Machine Learning, Hugging Face, or equivalent certifications.
• AWS Certified Machine Learning Specialty, AWS Certified AI Practitioner, or AWS Certified Solutions Architect certification.
• Experience documenting runbooks, supporting knowledge transfer, and promoting validated components from sandbox environments to production.
• Familiarity with enterprise security and compliance standards for production AI deployments.

Culture & Benefits

• Full-time employment model.
• Remote work model from Mexico.
• Production delivery with a focus on engineering rigor, operational controls, and knowledge transfer.