Thiago Silva

Senior

AI Engineer

Who I am?


Passion for Technology

Driven by a genuine passion for technology, I have built my career in dynamic and innovation-driven environments.

I enjoy exploring emerging technologies, solving complex problems, and transforming ideas into solutions that create real-world impact.

Enterprise AI Engineer

My journey evolved from Data Engineering and distributed systems to designing and delivering enterprise AI solutions.

By combining strong engineering foundations with Generative AI, I build scalable, secure, and production-ready systems that solve complex business challenges.

Global Collaboration

I thrive in multicultural environments and enjoy collaborating with teams and clients across the globe.

I believe the best solutions emerge when technical excellence, diverse perspectives, and strong communication come together toward a common goal.

What I've Delivered

Production-ready systems that improved efficiency, enabled better decisions, and created value for global organizations.

a person holding a smart phone and a credit card
Mastercard – Enterprise AI Assistant SDK

Designed and developed an enterprise AI Assistant SDK for Mastercard, enabling banks to integrate secure AI capabilities into their platforms. Implemented guardrails, PII protection, and responsible AI controls to ensure compliance, security, and production readiness for sensitive financial data.

a close up of a cell phone with icons on it
Microsoft – Copilot Studio Evaluation & AI Agents

Built and evaluated AI agents using Copilot Studio and real-world business scenarios. Developed analytics and performance frameworks that generated actionable feedback for Microsoft teams, helping improve agent orchestration, user experience, and platform capabilities.

Alberta Health – Healthcare AI Assistant

Led the development of a healthcare AI assistant capable of answering medical questions, providing location-based healthcare recommendations, promoting public health campaigns, and guiding users during emergency situations. Built with a strong focus on reliability, responsible AI, and user experience for a large-scale public healthcare environment.

Core Skills

Generative AI & LLMs

Building scalable and secure AI assistants and chatbots.

I design intelligent, multi-agent workflows that can autonomously solve complex enterprise tasks, prioritize user security, and deliver highly accurate information.

NLP, Embeddings & Vector Search

Transforming massive amounts of unstructured text into searchable, actionable knowledge.

I utilize vector databases and advanced embedding techniques to power lightning-fast, context-aware semantic search, enabling AI systems to deeply understand human language and deliver highly accurate, contextual responses.


Multimodal Generation

Architecting pipelines for the creation of synthetic audio, images, and videos. I build intelligent orchestrators capable of seamlessly combining different generative solutions into cohesive, highly engaging multimedia experiences.

Engineering & Architecture

Designing robust, high-performance architectures and microservices capable of supporting massive user concurrency. I build the essential APIs and automated data pipelines that seamlessly connect complex business logic with advanced AI models.

Cloud Infrastructure & DevOps

Deploying reliable, production-ready AI models into scalable cloud-based environments.

I implement automated continuous integration and delivery (CI/CD) pipelines to streamline updates, ensuring enterprise-grade stability and optimized performance.

Agile Delivery & Engineering Excellence

Driving the smooth execution of complex AI projects through Agile methodologies and structured task management via Jira.

I prioritize clean coding practices and comprehensive technical documentation, while fostering open, transparent communication across cross-functional teams to ensure alignment, continuous collaboration, and successful product delivery.

Tech Stack

A full breakdown of technologies, services, and libraries that I have experience with

Generative AI

Focusing on state-of-the-art implementation and orchestration.

Frameworks: LangChain, LlamaIndex, LangGraph, Langflow, CrewAI.

Model Providers: OpenAI (Since GPT-3), Anthropic, Google (Gemini), Mistral, Meta (Since Llama 2), AWS Bedrock.

Generative Media: ComfyUI (Custom Node Workflows), Stable Diffusion (XL/Flux.1), Midjourney, Google Veo, Runway Gen-3.

Techniques: RAG (Retrieval-Augmented Generation), Fine-tuning (LoRA), Prompt Engineering, Vision-Language Models (VLM).

Foundations: Embeddings (OpenAI, HuggingFace)

Responsible AI

Engineering defensive AI architectures, ensuring ethical governance through red teaming and automated guardrails.

Threat Mitigation: Prompt Injection (Direct & Indirect), Payload Splitting, Jailbreaking defense.

Red Teaming: Adversarial Testing, LLM Vulnerability Scanning, OWASP Top 10 for LLMs.

Guardrails: AWS Bedrock Guardrails, LangChain Guardrails, Data Anonymization, Content Filtering.

AI Observability & Evaluation

To monitor model performance, hallucination rates, and system latency.

Evaluation: LLM-as-a-Judge (G-Eval), DAG, QAG.

Benchmarking: Agentic Trajectory Accuracy, Hallucination Detection.

Tracing & Logging: Langfuse, LangSmith.

LMOps: Cost/Latency Analytics, Semantic Caching.

Data Engineering & ETL

Building high-throughput data pipelines and automated ETL processes

Orchestration: AWS Glue, Airflow, Argo Workflows.

Extraction: Scrapy, Selenium, Beautiful Soup.

Data Modeling, ETL Pipelines, Large Scale Datasets.

Databases & Vector Search

Designing hybrid storage strategies that combine traditional relational data with optimized vector search.

Storage: PostgreSQL, MongoDB, MySQL, Microsoft SQL Server.

Vector & Graph: ChromaDB, Neo4j, Amazon OpenSearch.

Cloud Storage: AWS S3, Azure Blob Storage, Google Cloud.

Computer Vision & ML

Extracting actionable insights from visual data through traditional image manipulation, custom OCR pipelines, and modern object detection architectures.


Vision: OpenCV, Detectron2, Tesseract OCR, GPT-Vision.

Frameworks: PyTorch, TensorFlow, Keras, Scikit-learn.

Processing: Video file manipulation, Pillow, NumPy, Word2Vec.

Cloud & Infrastructure

Managing scalable workloads

AWS Ecosystem: Amazon EC2, Bedrock, Lambda, S3.

Compute: Kubernetes, Docker, Linux.

Architecture: Microservices, Data Lakes.

MLOps & Deployment

Designing hybrid storage strategies that combine traditional relational data with optimized vector search.

Serving: FastAPI, Flask, Streamlit.

CI/CD: GitHub Actions , Argo Workflows , Canary, Version Control.

Messaging: RabbitMQ , Celery.

Software & Automation

Applying expert-level software engineering standards

Languages: Python, SQL, Batch Processing.

Tooling: SQLAlchemy, AsyncIO, Requests, PyQt5.

Quality: Pytest , Documentation, Poetry/Conda.