Senior AI/ML Engineer, PhD in AI Candidate
I’m Eric Ramirez, a Senior AI/ML Engineer focused on designing and deploying intelligent systems at production scale. I build AI architectures that integrate large language models, structured reasoning, and real-world constraints to produce reliable, high-signal outputs.
My work explores agentic systems, autonomous workflows, and emerging generative AI patterns, with an emphasis on evaluation, robustness, and system design rather than surface-level demos.
I hold a Master’s degree in Artificial Intelligence and Machine Learning and am currently pursuing a PhD in AI, where my research sits at the intersection of multi-agent orchestration, retrieval-augmented reasoning, and autonomous decision-making. I am building and formally evaluating systems where specialized agents perceive, plan, and act across extended task horizons, developing frameworks and architectures directly applicable anywhere that AI must perform consistently in high-stakes, low-feedback environments, with the goal of establishing the conditions under which autonomous AI can be trusted to execute end-to-end workflows with minimal human intervention.
This site showcases my applied systems, technical writing, and ongoing research into the next generation of intelligent architectures.
Technical Depth
- Large Language Model (LLM) systems & advanced NLP pipelines
- Agentic architectures using LangChain, LangGraph, & multi-agent orchestration
- Retrieval-Augmented Generation (RAG) with grounded knowledge retrieval and structured outputs
- Evaluation frameworks for LLM reliability (hallucination mitigation, guardrails, traceability)
- Hybrid AI systems combining deterministic logic, ML models, and probabilistic reasoning
- ML system design & MLOps (data pipelines, model lifecycle, observability, evaluation)
- Distributed AI deployment across cloud environments (Azure, AWS, containerized inference)
- AI governance, safety, and auditability in production decision systems
I design systems end-to-end — ingestion, retrieval, reasoning, decision layers, and traceable outputs suitable for real-world deployment.
Where I Create Leverage
Technical skill builds systems.
Communication builds adoption.
My background in sales and management trained me to:
- Translate AI complexity into clear business decisions
- Align engineering, product, compliance, and leadership
- Set realistic expectations around AI capabilities and risk
- Build trust in regulated and high-stakes environments
- Move initiatives forward in ambiguous, multi-stakeholder settings
My PhD research focuses on governance and human oversight in advanced AI systems, studying how organizations deploy increasingly autonomous technologies safely, responsibly, and at scale.
Most AI projects fail at the communication and governance layer, not the model layer.
I operate at that boundary.
Latest Writings
Get in Touch
Contact me for research collaboration or industry opportunities.