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Adrian Garcia

Verified Expert in Engineering

Back-end and AI Engineer Developer

Merced, CA, United States

Toptal member since December 30, 2025

Expertise

Git Software Development API Back-end Developers Algorithms Machine Learning Full-stack Deep Learning Artificial Intelligence RAG NLP

Bio

Adrian is a senior back-end engineer with 8+ years of experience building cloud-native platforms for AI, ad tech, healthcare, and fintech. He delivers end-to-end solutions—from microservices to full stack—using Python, Go, and TypeScript/Node.js. His expertise spans event-driven REST and gRPC systems and NLP and LLM back ends, including RAG, fine-tuning, and vector search. Adrian has deployed production stacks on AWS, GCP, and Azure, with a focus on reliability and observability.

Portfolio

Harvest LLC

Go, Python, FastAPI, REST, gRPC, Redis, PostgreSQL, Firebase...

Citadel LLC

Node.js, TypeScript, Express.js, NestJS, BullMQ, Redis, RabbitMQ, Docker...

Convoy

Python, FastAPI, Apache Airflow, SpaCy, Transformers, PyTorch, TensorFlow...

Experience

Python - 10 years
System Design - 8 years
Node.js - 8 years
Back-end Development - 8 years
PostgreSQL - 8 years
Artificial Intelligence (AI) - 6 years
Apache Kafka - 6 years
Go - 5 years

Preferred Environment

MacOS, Windows, GitHub, Google Cloud Platform (GCP), Amazon Web Services (AWS), Large Language Models (LLMs), Python 3, Go, Node.js, BERT

The most amazing...

...thing I've built is a production-grade NLP entity extraction service on Kubernetes with autoscaling and observability, sustaining 10,000+ requests per minute.

Work Experience

Senior Back-end & AI Engineer

2025 - 2025

Harvest LLC

Built Go and FastAPI microservices with OAuth 2, JSON Web Tokens (JWT), RBAC, rate limiting, retries, and tracing.
Delivered REST and gRPC APIs and improved stability under load via pagination, backpressure, and pooling.
Implemented Redis caching and concurrency tuning to reduce P95 latency during traffic spikes.
Built ETL/ELT pipelines with data duplication, schema-drift detection, and validation suites to improve data SLAs.
Deployed to Amazon ECS/EKS with autoscaling and zero-downtime rollouts. Added CI/CD safety checks.
Implemented internal RAG and semantic search using LangChain and Pinecone with guardrails and cost control.
Integrated Thrift into microservices for cross-language communication between services written in Go and Python.
Defined data models and service interfaces using Thrift's IDL, enabling efficient communication and reducing latency in distributed systems.
Managed delivery execution in Jira and collaborated with back-end, QA, and product teams to define requirements, deliver features end-to-end, and improve reliability through testing, monitoring, and iterative improvements.

Technologies: Go, Python, FastAPI, REST, gRPC, Redis, PostgreSQL, Firebase, Amazon S3 (AWS S3), Parquet, Amazon EKS, Amazon Elastic Container Service (ECS), OpenTelemetry, OpenAI, CI/CD Pipelines, LangChain, Pinecone, Agile, Kubernetes, Slack, Visual Studio Code (VS Code), JetBrains Rider, GoLand, GitLab, Bitbucket, Repository Management, Jira, Kanban, NumPy, Pandas, Machine Learning, Software Development, MLflow, Weaviate, SpaCy, Transformers, TensorFlow, Hugging Face, Monitoring, Swagger, OpenAPI, OAuth 2, JSON Web Tokens (JWT), GitHub Actions, GitHub, Grafana, Prometheus, Celery, Echo, Gin, Go Kit, Fine-tuning, NVIDIA TensorRT, AWS Batch, AWS Lambda, Full-stack Development, Software Architecture, Microservices Architecture, Document Parsing, BERT, Python 3, Large Language Models (LLMs), Back-end Admin Systems, Back-end Architecture, Back-end Development, Next.js, Retrieval-augmented Generation (RAG), Pydantic, WebSockets, Data Scientist, Back-end, Back-end APIs, AWS IoT, Data Science, Conversational AI, Natural Language Processing (NLP), RESTFul APIs, APIs, Prompt Engineering, Artificial Intelligence (AI), AI Agents, Microservices, Vector Databases, OpenAI API, Caching, API Observability, ETL, ELT, Ollama, Embeddings from Language Models (ELMo), API Design, Concurrency, Orchestration, Logistic Regression, REST APIs, Asyncio, Time Series, Linear Regression, Scikit-learn, K-means Clustering, AI Chatbots, Data Protection, Mistral AI, API Integration, Data Visualization, Vercel, Agentic AI, Chatbots, Amazon Bedrock, ChatGPT, Large-scale Projects, Real-time Systems, Claude API, Anthropic, Claude

Back-end Engineer

2023 - 2025

Citadel LLC

Designed high-reliability Node.js and TypeScript services using event-driven architecture for regulated workflows.
Built fault-tolerant ingestion pipelines with BullMQ/Redis and RabbitMQ worker queues and rate limiting.
Developed document-intelligence microservices using LLMs plus custom named entity recognition and key information extraction pipelines.
Implemented MLOps automation using MLflow, GitOps, and CI/Terraform for reproducible deployments.
Built RAG and semantic search APIs using vector databases—pgvector/Pinecone/Weaviate—and GraphRAG with Neo4j.
Added service-mesh security and full-stack observability—mTLS, OpenTelemetry, dashboards.
Designed and developed high-performance Go microservices for data ingestion, processing pipelines, and real-time data analytics, integrating with Cassandra for large-scale, distributed data storage.
Optimized Cassandra queries and data models to ensure efficient reads and writes in high-velocity systems, supporting high-throughput, low-latency needs in data-driven applications.

Technologies: Node.js, TypeScript, Express.js, NestJS, BullMQ, Redis, RabbitMQ, Docker, Kubernetes, Terraform, OpenTelemetry, Apache Airflow, Temporal Cloud, MLflow, Pgvector, Pinecone, Weaviate, Neo4j, Slack, Windows Subsystem for Linux (WSL), Linux, MacOS, Windows, Visual Studio Code (VS Code), GoLand, JetBrains Rider, GitLab, Bitbucket, Repository Management, Jira, Agile, Kanban, Google Cloud Platform (GCP), Amazon Web Services (AWS), NumPy, Software Development, REST, PostgreSQL, Amazon Elastic Container Service (ECS), Amazon EKS, PyTorch, FAISS, Swagger, OpenAPI, JSON Web Tokens (JWT), GitHub Actions, GitHub, Grafana, Prometheus, Apache Kafka, AWS Lambda, AWS IoT, Software Architecture, Microservices Architecture, Back-end Architecture, Back-end Development, Google Kubernetes Engine (GKE), Cassandra, Amazon DynamoDB, WebSockets, Azure, Back-end APIs, RESTFul APIs, APIs, n8n, Microservices, API Observability, API Design, Fault Tolerance, Concurrency, REST APIs, Time Series Analysis, K-means Clustering, AI Chatbots, Data Protection, Mistral AI, API Integration, LangGraph, Azure ML Studio, Neural Networks, Auto Encoder, GraphQL, Apache Cassandra, Go, Claude API, Anthropic, Claude

Senior AI & GenAI Engineer

2022 - 2024

Convoy

Architected an end-to-end ingestion pipeline for legal PDFs/HTML with embeddings and FAISS indexing.
Built dense retrieval and reranking workflows to increase context precision and retrieval quality.
Delivered RAG-driven Q&A microservices in FastAPI, packaging retrieval and prompts into low-latency APIs.
Implemented continuous refresh pipelines via AWS Lambda and S3 events for re-embedding and index updates.
Designed GPU-accelerated inference environments with Docker, Kubernetes, and TensorRT for throughput and latency.
Built evaluation and governance frameworks and secured endpoints or storage for sensitive documents.

Technologies: Python, FastAPI, Apache Airflow, SpaCy, Transformers, PyTorch, TensorFlow, FAISS, LangChain, Hugging Face, AWS IoT, AWS Lambda, AWS Batch, Docker, Kubernetes, NVIDIA TensorRT, Terraform, Fine-tuning, Slack, Linux, Windows, MacOS, Windows Subsystem for Linux (WSL), JetBrains Rider, Visual Studio Code (VS Code), GoLand, GitLab, Repository Management, Bitbucket, Jira, Waterfall, NumPy, Machine Learning, Software Development, OpenAI, MLflow, GitHub, Celery, Deep Learning, Document Parsing, BERT, Python 3, Retrieval-augmented Generation (RAG), Milvus, Back-end, Conversational AI, Natural Language Processing (NLP), Prompt Engineering, Artificial Intelligence (AI), Vector Databases, OpenAI API, Ollama, Embeddings from Language Models (ELMo), Fault Tolerance, Logistic Regression, Asyncio, Time Series, Time Series Data, Time Series Analysis, Scikit-learn, Data Protection, Mistral AI, API Integration, Vercel, Agentic AI, Chatbots, Amazon Bedrock, ChatGPT, Azure ML Studio, Binary Classification Models, Neural Networks, Auto Encoder, Large-scale Projects

Senior Back-end and Data Science Engineer

2019 - 2022

Zillow

Designed and built Go back-end microservices for adtech bidding systems, optimizing for low latency, high availability, and real-time performance.
Developed Kafka streaming pipelines to process impressions, clicks, and conversions in real time, supporting advertiser decisioning workflows.
Implemented Go Kafka consumer groups with partitioning, offset management, and reliable event processing for high-QPS systems.
Delivered low-latency data access using PostgreSQL, Cassandra, and Redis for high-frequency queries and ad targeting.
Integrated fraud screening with GeoIP validation and double verifier services for real-time bidding decisions.
Optimized real-time bidding algorithms and social network enrichment to enhance ad targeting and improve conversion rates.
Worked on ad delivery optimization with social network data for accurate advertising personalization.
Containerized Go services with Docker, deployed on Kubernetes, and established CI/CD pipelines using GitHub Actions.
Leveraged event-driven microservices to scale real-time ad decisioning systems and integrated Thrift into the microservices architecture for cross-language communication between Go, Python, and Java services.
Gained proficiency in GraphQL, building high-performance APIs for large-scale adtech systems and social network data processing.

Technologies: Go, Go Kit, Gin, Echo, Python, FastAPI, Celery, Apache Kafka, RabbitMQ, Redis Streams, PostgreSQL, Redis, MongoDB, gRPC, Prometheus, Grafana, GitHub, GitHub Actions, Docker, Kubernetes, Slack, MacOS, Windows, Windows Subsystem for Linux (WSL), Linux, Visual Studio Code (VS Code), GoLand, JetBrains Rider, GitLab, Repository Management, Bitbucket, Jira, Agile, Kanban, Amazon Web Services (AWS), Google Cloud Platform (GCP), Pandas, Software Development, REST, Amazon S3 (AWS S3), Parquet, Pgvector, Monitoring, Swagger, Fine-tuning, AWS IoT, Software Architecture, Microservices Architecture, Back-end Admin Systems, Back-end Architecture, Back-end Development, Google Kubernetes Engine (GKE), Pydantic, Cassandra, Amazon DynamoDB, WebSockets, Data Scientist, Back-end APIs, Data Science, Conversational AI, Natural Language Processing (NLP), RESTFul APIs, APIs, Web Scraping, Artificial Intelligence (AI), Microservices, Caching, API Observability, Scraping, ETL, ELT, Embeddings from Language Models (ELMo), API Design, Orchestration, REST APIs, Asyncio, Time Series, Time Series Data, Time Series Analysis, Linear Regression, Scikit-learn, K-means Clustering, AI Chatbots, Data Protection, Mistral AI, Data Visualization, Chatbots, GraphQL, Large-scale Projects, Real-time Systems, Apache Cassandra, Claude

Full-stack Engineer

2017 - 2019

Twills

Re-architected and scaled an eCommerce back end using Node.js and PHP services, delivering ordering, accounts, and catalog APIs supporting 1,000+ daily users.
Built and maintained back-end services in Symfony/Laravel and C#/.NET for payments, admin tooling, and internal operations workflows.
Implemented enterprise security controls, including JWT/OAuth 2, RBAC, idempotent webhooks, audit logs, and rate limiting across services.
Integrated payments, shipping, and inventory providers via OpenAPI contracts to standardize partner integrations and reduce integration defects.
Tuned MySQL with indexing, query optimization, and connection pooling to improve P95 latency and reduce system load.
Introduced Docker/VMware-based environments and CI/CD pipelines for repeatable deployments; added centralized logging, monitoring, alerts, and disaster recovery runbooks.

Technologies: Node.js, TypeScript, JavaScript, Express.js, Symfony, Laravel, C#.NET, Redis, JSON Web Tokens (JWT), OAuth 2, OpenAPI, Swagger, Docker, CI/CD Pipelines, Monitoring, PHP, Slack, JetBrains Rider, GoLand, Visual Studio Code (VS Code), GitLab, Repository Management, Bitbucket, Software Development, NestJS, BullMQ, GitHub, Full-stack Development, Software Architecture, Back-end Admin Systems, Back-end Development, Front-end Development, React, Next.js, Back-end APIs, AWS IoT, RESTFul APIs, APIs, n8n, Scraping, ELT, API Design, Concurrency, REST APIs, Data Visualization, C#, GraphQL, Large-scale Projects, Real-time Systems

Experience

AI Data Visualization Platform (MVP)

Built an AI-driven data visualization and Q&A platform with a distributed back end: Node.js (NestJS/Express) for core APIs and Python/FastAPI, and Go microservices for AI workflows. I implemented ingestion pipelines to collect, normalize, and index high-volume economic datasets, such as the World Bank's WDI, the IMF, and Eurostat, with consistent schemas and reliable query performance. I added vector-search using Pinecone and integrated OpenAI-powered reasoning through FastAPI endpoints. I also implemented secure, high-availability operations with idempotent APIs, JWT/OAuth 2 authentication, caching, and rate limiting. Finally, I added detailed logging, tracing, and performance monitoring for latency, throughput, and cost observability.

Company Data Analytics

Developed an end-to-end analytics pipeline combining Node.js back-end services with Python/FastAPI machine learning components to scrape, clean, and transform company data from Glassdoor and corporate websites. I orchestrated automated workflows using Airflow DAGs with dependencies, retries, alerting, and self-healing for embedding/model failures. I also generated semantic embeddings using an Ollama LLM and deployed predictive models, including logistic regression and gradient-boosted trees, to evaluate stability, risk, and growth potential. I automated reporting through Jupyter/Quarto for reproducible insights and model explanations, and exposed embeddings and predictions via REST APIs. Lastly, I implemented data-quality controls—deduplication, schema validation, and consistency checks—to improve reliability and pipeline SLAs.

Multi-agent DAG Orchestration Back End

Built a FastAPI and asyncio back end to orchestrate multi-agent pipelines modeled as DAGs. I implemented parallel execution, conditional routing, and fault-tolerant recovery to support robust long-running workflows. I also designed clean API endpoints to submit runs, track state, and manage execution flow across steps, with a focus on reliability and extensibility for agent-based automation.

Education

2014 - 2019

PhD in Material Science (Focused on Computational Science and Data Science)

University of California, Irvine - Irvine, CA, USA

2012 - 2014

Master's Degree in Engineering (Focused on Scientific Computing and Analytics)

University of California, Irvine - Irvine, CA, USA

2008 - 2012

Bachelor's Degree in Mechanical Engineering (Focused on Programming and Modeling)

University of California, Irvine - Irvine, CA, USA

Certifications

Tools

GoLand, Jira, Slack, Amazon Elastic Container Service (ECS), RabbitMQ, Terraform, Apache Airflow, Go Kit, Celery, Grafana, GitHub, GitLab, Bitbucket, JetBrains Rider, Amazon EKS, Google Kubernetes Engine (GKE), ChatGPT, Claude, AWS Batch, Jupyter, n8n, Azure ML Studio

Languages

Python, Go, TypeScript, JavaScript, Python 3, GraphQL, C++, C#.NET, PHP, C#

Frameworks

gRPC, Express.js, NestJS, Gin, Echo, JSON Web Tokens (JWT), OAuth 2, Swagger, Next.js, LangGraph, Symfony, Laravel

Paradigms

Agile, Kanban, REST, Microservices, API Observability, ETL, Microservices Architecture, Back-end Architecture, Real-time Systems

Platforms

Docker, Visual Studio Code (VS Code), Firebase, Kubernetes, AWS IoT, AWS Lambda, Apache Kafka, Ollama, MacOS, Linux, Windows, Amazon Web Services (AWS), Azure, Vercel, Temporal Cloud, Google Cloud Platform (GCP)

Storage

Redis, PostgreSQL, Amazon S3 (AWS S3), Neo4j, MongoDB, Cassandra, Amazon DynamoDB, Data Validation

Other

Windows Subsystem for Linux (WSL), Repository Management, Waterfall, Machine Learning, Scientific Computing, Data Processing, Software Development, System Design, Computational Modeling, FastAPI, OpenTelemetry, OpenAI, CI/CD Pipelines, LangChain, Pinecone, BullMQ, MLflow, Pgvector, Weaviate, Transformers, FAISS, Hugging Face, Fine-tuning, Redis Streams, Prometheus, GitHub Actions, Vector Databases, Caching, Scraping, ELT, Logistic Regression, Orchestration, Concurrency, API Design, Full-stack Development, Software Architecture, Deep Learning, Large Language Models (LLMs), BERT, Document Parsing, Back-end Development, Back-end Admin Systems, Problem Solving, Algorithms, Artificial Intelligence (AI), Back-end, Retrieval-augmented Generation (RAG), Milvus, WebSockets, Conversational AI, Natural Language Processing (NLP), RESTFul APIs, APIs, Prompt Engineering, AI Agents, Time Series, Time Series Data, Time Series Analysis, Linear Regression, K-means Clustering, AI Chatbots, Data Protection, Mistral AI, API Integration, Data Visualization, Agentic AI, Chatbots, Amazon Bedrock, Large-scale Projects, Anthropic, Numerical Methods, R Programming, Parquet, NVIDIA TensorRT, Monitoring, Gradient Boosting, Quarto, Fault Tolerance, Front-end Development, Data Science, Data Scientist, Web Scraping, Binary Classification Models, Neural Networks, Auto Encoder, Apache Cassandra, Embeddings from Language Models (ELMo)

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