As an AI Software Engineering Consultant with 10+ years of experience, I partner with companies to design, build, and scale intelligent, high-performance systems.
My core strength lies in leveraging Python, Go, and Rust, underpinned by deep software architecture expertise and hands-on execution, to turn complex AI concepts into robust, production-ready solutions that create real business value.
I specialize in translating ambitious business requirements into cutting-edge, cloud-native applications—particularly where AI/ML meets real-world constraints. This includes building AI-powered features, optimizing MLOps pipelines, and architecting distributed systems for real-time data processing.
Whether the solution requires custom development or fast automation using low-code tools like n8n or Make, my focus remains on delivering scalable, maintainable, and results-oriented systems. I adapt the technology stack to the business need, not the other way around.
I apply a “best-tool-for-the-job” approach:
- Python for its rich AI/ML ecosystem
- Go for concurrency, speed, and service reliability
- Rust for performance-critical and safety-sensitive components
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AI/ML System Design & Implementation: End-to-end pipelines, model integration, scalable deployment
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Scalable Architecture & Microservices: Designing resilient, decoupled systems that evolve with your business
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High-Performance Backend Systems: Building fast, optimized services critical for AI-driven applications
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Event-driven & Real-Time Pipelines: Kafka, Apache Beam and BigQuery for reliable data flow and insight generation
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Cloud-Native & DevOps: GCP, AWS, Kubernetes, Terraform for modern, automated infrastructure
-Extensive experience with GCP, AWS, Kubernetes, Terraform, BigQuery, and Dataflow.
- Optimizing high-throughput data pipelines with DuckDB, Apache Beam, Spark, and Flink.
- Infrastructure as Code (IaC) with Terraform & Github Action
- Extensive experience with GCP, AWS, Kubernetes, Terraform, BigQuery, and Dataflow.
- Optimizing high-throughput data pipelines with DuckDB, Apache Beam, and Flink.
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Python: Expertise in building APIs, microservices, and data pipelines using:
- FastAPI, Flask, Django for RESTful and async APIs.
- Pandas, Polars, and DuckDB for high-performance data analysis.
- Celery & Redis for distributed task processing.
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Golang: High-performance applications and microservices using:
- Gin, Echo, and Chi for API development.
- gRPC & Protobuf for efficient inter-service communication.
- Fiber & Kratos for scalable web applications.
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Rust: Exploring performance-critical system-level applications.
- BigQuery: Optimized data warehousing and analytics solutions.
- Apache Beam & Dataflow: Real-time & batch data processing pipelines.
- Dbt & Dataform: Automating data transformation & orchestration in SQL-based pipelines.
- Flink & Spark: High-performance stream processing for big data.
- DuckDB: Local-first OLAP analytics for fast in-memory queries.
- LLMs (Large Language Models) → Experience integrating OpenAI, LangChain, and custom AI models into applications.
- Java & Kotlin: Backend services with Spring Boot, Quarkus, and Micronaut.
- Vue & React: Creating modern, interactive, and scalable front-end solutions.
- React Native & Flutter: Cross-platform mobile applications.
- PostgreSQL, MongoDB, and Redis: Designing and optimizing databases.
- Docker & Kubernetes: CI/CD automation and cloud-native deployments.
- GraphQL & REST APIs: Building efficient and flexible data interfaces.
- 🔭 Currently enhancing software solutions at UKG.
- 🌱 Deepening my Python, Golang, Rust, Java, Kotlin, and Vue expertise.
- 👯 Eager to contribute to open-source projects and innovative teams.
- LinkedIn: Duany Baró Menéndez
- Github: macurandb
I'm always open to interesting conversations and collaboration opportunities. Feel free to reach out if you're working on something exciting or want to chat about technology!