Data & AI Engineer with 4+ years building production-grade data pipelines and LLM-powered systems - GPU inference, RAG, and fault-tolerant ETL on Kubernetes. Applied-mathematics background, focused on reliable, scalable, high-impact data solutions.
Experience
AccentureJul 2026 - Present
Data Engineering, Management & Governance Analyst
Data engineering, management and governance for enterprise-scale data platforms.
Domus Capital - Precatórios / Ativos JudiciaisApr 2023 - Apr 2026
Data & AI Engineer
Built scalable Python data pipelines and backend services for production data/AI workflows.
Developed an OCR engine in Python powered by LLM inference with Redis, FastAPI and GPU processing.
Shipped async document-processing that summarizes large legal documents and emails automated decisions.
Built near-real-time ingestion pipelines with Apache Kafka, streaming from multiple upstream sources.
Modeled data in SQL across a layered architecture for analytics (core, semantic, metrics).
Orchestrated Airflow on Kubernetes; cut AWS cost via S3 lifecycle policies and ECR automation.
Dolomites ConsultoriaNov 2022 - Apr 2023
Data Engineer
Designed containerized ETL pipelines in Python processing payment data from many Brazilian state & municipal sources.
Orchestrated 100+ Docker tasks per run with Airflow on Kubernetes; automated DAG deployment via GitHub with centralized logging in S3; queried processed data with SQL.
Laguz OpportunitiesMar 2022 - Nov 2022
Data Engineer
Built automated Selenium crawlers in Python to extract legacy legal documents; parsed scanned PDFs (Tesseract, Textract, Camelot, Tabula).
Built ETL into a layered S3 data-lake, querying with SQL; contributed Power BI dashboards for business decision-making.
Selected Project
AI Platform EngineeringSelf-directed · 2026
Agentic AI platform (hexagonal architecture): MCP tools in Python, RAG with Titan V2 embeddings over pgvector/HNSW, LangGraph agents with tool calling, OpenTelemetry observability. github.com/SoltanovM/LeIA ↗