Israel Ayala Illan
Summary
Innovative Software Developer with expertise in Python and system design, specializing in autonomous LLM-based agents. Proven track record of enhancing reasoning quality and reducing latency through optimized retrieval-augmented generation pipelines. Demonstrated ability to collaborate with cross-functional teams, driving impactful research initiatives and project outcomes. Skilled in model evaluation and performance optimization to deliver high-quality software solutions.
Overview
1
1
year of professional experience
Work History
Software Developer
Aosenuma
10.2024 - Current
- Designed and implemented autonomous LLM-based agents with multi-step reasoning, tool use, and memory using Python, LangChain, and LlamaIndex.
- Integrated and evaluated state-of-the-art LLMs (OpenAI, Anthropic, and open-source models), focusing on reasoning quality, latency, and reliability in production environments.
- Architected retrieval-augmented generation (RAG) pipelines leveraging vector databases (Pinecone, FAISS) for semantic search and long-context retrieval.
- Built automation and orchestration pipelines connecting LLM agents to external APIs and services, enabling scalable task execution and rapid experimentation.
- Optimized agent performance through prompt design, retrieval strategies, and memory management, improving factuality, relevance, and contextual coherence.
- Authored technical documentation detailing system architecture, experimental setup, and design trade-offs; collaborated remotely with cross-functional teams on research-driven projects.
Education
Bachelor of Science - Electronic Engineering
Universidad Autonoma De San Luis Potosi
San Luis Potosí City, San Luis Potosí, Mexico10-2023
Skills
- Python
- Data Structures & Algorithms
- System Design
- API Design (REST)
- Multithreading & Concurrency
- CI/CD Pipelines
- Retrieval-Augmented Generation (RAG)
- Vector Databases & Semantic Search
- Model Evaluation & Performance Optimization
Projects
AI-Powered ESG Intelligence Platform (Internal)
Research / Software Engineering Project
- Designed and implemented a production-grade AI platform for transforming heterogeneous sustainability documents into a unified, queryable knowledge system.
- Built multi-format data ingestion and ETL pipelines to process structured and unstructured documents (e.g., reports, spreadsheets), enabling automated extraction of domain-specific metrics.
- Architected a retrieval-augmented generation (RAG) system combining semantic search and language models to support natural-language querying over long-form documents.
- Developed entity and relationship extraction pipelines to model document knowledge as structured representations, enabling advanced querying and pattern discovery.
- Integrated vector-based retrieval for low-latency semantic search and hybrid analytical workflows across tabular and narrative data.
- Focused on scalability, reliability, and maintainability, delivering a modular, cloud-ready system with testing pipelines and access control.
Tech: Python, LLMs, RAG, Semantic Search, Vector Databases, ETL Pipelines, API-Driven Systems.
Timeline
Software Developer
Aosenuma
10.2024 - Current
Bachelor of Science - Electronic Engineering
Universidad Autonoma De San Luis Potosi