Role: Consultant AI Engineer

Required Qualifications

Minimum 5+ years of software engineering experience, including at least 2 years focused on AI/ML, LLM applications, or agentic systems.
Proven track record of shipping LLM, AI/ML, or agentic AI solutions into production, preferably on AWS.
Strong hands-on experience in Agentic AI and multi-agent orchestration using production agent frameworks such as AWS Strands SDK, LangGraph, CrewAI, or Claude Agent SDK.
Experience designing and implementing ReAct / tool-use loops, supervisor-based orchestration, DAG orchestration, state management, selective re-execution, and human-in-the-loop approval gates.
Hands-on experience with Amazon Bedrock and AWS GenAI stack, including foundation models, Knowledge Bases, Agents, S3, Lambda, IAM, ECS/EKS, or SageMaker.
Experience deploying, scaling, and managing GenAI solutions on AWS with appropriate cost, security, and operational controls.
Hands-on experience integrating AI agents with enterprise systems using Model Context Protocol / MCP, function calling, REST APIs, issue trackers,



source control systems, or test management platforms.
Strong experience building RAG and hybrid retrieval solutions using vector databases such as OpenSearch or similar platforms.
Experience with embeddings, semantic chunking, hierarchical chunking, metadata design, taxonomy design, hybrid retrieval, re-ranking, and retrieval-failure verification.
Strong understanding of transaction-safe tool integration, including atomic commit, rollback handling, and prevention of partial-write or inconsistent-state failures.
Strong experience in prompt engineering and evaluation, including prompt development, versioning, regression testing, few-shot example curation, golden sets, benchmark sets, and A/B testing.
Experience defining and tracking evaluation metrics for accuracy, hallucination, factual consistency, cost, and performance improvement across model iterations.
Experience with LLMOps / MLOps practices incl

📌 AI Engineer (México)
🏢 Ltm
📍 México