AI Architect – Agentic Systems (LLM & Multi-Agent Solutions)
Monterrey, Nuevo León, Mexico
MXN 720K-1062K (estimate) Senior-level Full Time
Tasks
- Define memory strategies
- Design multi-agent architectures
- Establish observability tracing feedback loops
- Evaluate and improve LLM reliability and accuracy
- Implement controls for agent behavior
- Implement model cost security privacy guardrails
- Integrate AI into core enterprise systems
- Integrate LLM powered agents with APIs and tools
- Integrate LLM powered agents with enterprise data platforms
- Integrate LLM powered agents with operational workflows
- Lead agentic systems from PoC to production
- Orchestrate agent coordination patterns
- Train teams on best practices for scalable AI systems
Perks/Benefits
- Career coaching
- Coaching
- Employee assistance program
- Flexible working hours
- Global career opportunities
- Hybrid work
- Training opportunities
- Wellbeing program
Skills/Tech-stack
AI Foundry | API Integration | AWS | Agent Framework | Agent coordination | Agent systems | Amazon Bedrock | Azure AI | Azure AI Foundry | Context grounding | Context window | Context window management | CrewAI | Distributed Systems | Driven systems | Event Driven | Event Driven Systems | Feedback loops | Function Calling | Google Vertex | Google Vertex AI | Hallucination mitigation | Information Retrieval | LLM orchestration | Langchain | Language Models | Large Language Models | Memory Management | Multi-Agent | Multi-Agent Systems | Observability | Python | RAG evaluation | Retrieval optimization | Retrieval-Augmented Generation | Semantic Kernel | Software Architecture | Text Embeddings | Tokenization | Tool use | Tracing | Transformer Architecture | Vector Representations | Vertex AI | Window management
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Architect | Architect | Engineer | Learning Engineer | Machine Learning Engineer
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