Forward-Deployed Engineer · Applied AI · Enterprise AI Systems
📍 Brasília, Brazil
11+ years shipping production AI systems. 5+ years embedded with enterprise customers as a Forward-Deployed Engineer. I specialize in turning ambiguous customer problems into reliable agentic LLM systems — from discovery through compliance-aware deployment.
Results shipped across fintech, edtech, healthcare, and government
Deep technical capability across the full AI delivery stack
MCP servers, sub-agents, skill libraries, planning / execution / verification / recovery layers, tool orchestration, memory systems, reasoning loops
Customer discovery, system boundary design, secure integration contracts, white-glove production deployment in compliance-heavy environments, stakeholder partnership
Model benchmarking (Claude, GPT, Gemini), scenario test sets, regression checks, structured telemetry, step-level execution tracing, LLM evaluation frameworks
FastAPI, Kafka, Spark, Databricks, Airflow, vector databases, RAG pipelines, embedding systems, semantic search, ETL optimization
Production deployments on AWS (Lambda, ECS, SageMaker) and GCP. Infrastructure-as-code with Terraform and Docker. Observability with Datadog. Continuous delivery via GitLab CI/CD with zero-downtime release discipline.
Codifying repeatable deployment playbooks, feeding customer learnings back into product and engineering, mentoring engineers, cross-functional delivery leadership
11+ years building and deploying production AI systems
High-impact systems shipped end-to-end
Production agentic workflows deployed in compliance-heavy customer environments
Embedded as FDE to design and ship MCP servers, sub-agents, and reusable skill libraries. Established system boundaries, integration contracts, and evaluation gates for autonomous AI workflows operating on sensitive healthcare data.
15 min → ~90 sec average resolution time via autonomous AI pipeline
Redesigned exception management from scratch as an event-driven AI pipeline. ML classifier predicts resolutions; autonomous agents execute workflows at confidence threshold, eliminating human intervention for recurring patterns.
~80% user engagement increase across a B2B enterprise client base
Led 6-engineer team to build a GenAI platform generating personalized multimodal learning content (listening, speaking, reading, writing). Included ASR-based pronunciation scoring, rubric-aligned writing feedback with bias mitigation, and article-aware comprehension generators.
~15x search latency reduction · Millions of indexed articles
Built a hybrid semantic search system using SciBERT and multilingual embeddings. Combined BM25, citation metrics, recency decay, and author authority with learning-to-rank models to serve millions of researchers across Brazil's academic network.
Computer Science, University of Brasília (UnB)
Multi-agent strategic simulation, autonomous decision-making, and adversarial agent behavior with Game Theory for Environmental Simulation
Rational agent architectures with Belief–Desire–Intention (BDI) frameworks
Multi-agent systems for environmental management simulation
Ph.D. research in multi-agent systems and autonomous decision-making — the foundational theory behind modern agentic AI systems
Technologies I ship production systems with
The human behind the agentic pipelines
Powered by Nintendo since 198x. (That's me in the photo — you can't really see it, but it's a Nintendo 64 t-shirt.)
Spent 4 years teaching autonomous agents to outsmart each other using Game Theory. Called it a PhD.
Born in Belem, based in Brasília, fluent in English, native in Python. C2 certified — the accent comes free of charge.
Favorite side effect of being a Forward-Deployed Engineer: shipping AI in hospitals, banks, and edtechs — sometimes in the same sprint.
I'm looking for Forward-Deployed Engineer and Applied AI roles at ambitious AI companies. I bring production-tested agentic systems experience and a track record of delivering reliably inside complex enterprise environments.