Gabriel – AI agent development, Golang, Kubernetes

An open-source AI inference infrastructure platform supporting local GenAI and image-generation workloads across AMD and NVIDIA environments. The product provides runtime capabilities for model inference, image upscaling, GPU execution, profiling, and performance benchmarking, enabling efficient and reliable AI workloads on local hardware.

• Led design and implementation of high-throughput distributed data platforms for AI-facing and crypto-native systems.
• Built and optimized backend services in Golang and C++, with PostgreSQL as the primary datastore.
• Designed data ingestion and processing pipelines feeding ML training, inference, and blockchain analytics.
• Optimized SQL performance through query planning, indexing, schema design, and EXPLAIN / ANALYZE.
• Engineered systems with strict transactional guarantees, consistency models, WAL behavior, and low-latency requirements.
• Implemented performance-critical components on hot paths, optimizing throughput, tail latency, and resource usage.
• Architected streaming data pipelines using Kafka and deployed them at scale on Kubernetes in AWS.
• Ensured fault tolerance, replayability, and deterministic processing for AI and crypto workloads.
• Integrated observability with Prometheus and Grafana for latency SLOs, pipeline health, and database metrics.
• Built RPC and REST APIs consumed by AI services, analytics layers, and distributed crypto systems.
• Applied blockchain-inspired principles such as determinism, data integrity, and fault tolerance to off-chain systems.
• Designed and led a Decentralized Identity Management System (DIMS).
• Aligned the identity system with W3C DID concepts, including decentralized identifiers, key management, and trust models.
• Applied cryptography including ECDSA, hashing, and privacy-preserving techniques to identity systems.

A high-performance backend and distributed systems platform focused on data processing, reliability, and production performance. The platform supports scalable services and data-intensive workloads through efficient transaction processing, asynchronous operations, failure handling, and production observability, with an emphasis on scalability, resilience, and maintainability.

• Contributed hands-on to the design and delivery of high-performance backend and distributed systems in an enterprise energy and trading environment.
• Worked primarily with C++ and Golang on performance-critical services and data- and AI-driven platforms.
• Designed and operated backend services using PostgreSQL, focusing on data processing, transaction behavior, indexing strategies, query planning, and performance under load.
• Analyzed and optimized database access patterns using EXPLAIN / EXPLAIN ANALYZE, schema design, and index tuning.
• Built systems sensitive to data consistency, latency, and throughput trade-offs in production environments.
• Implemented and optimized C++ components on performance-critical data paths, focusing on memory efficiency, low latency, and high throughput.
• Investigated bottlenecks related to contention, connection management, and resource saturation in data-driven workloads.
• Built scalable backend services in Golang with Kafka-based messaging and deployment on Kubernetes in AWS, ensuring fault tolerance and predictable performance.
• Worked on system design decisions involving back-pressure, asynchronous processing, and failure handling.
• Used Prometheus and Grafana to monitor database performance, data pipelines, service latency, and system health.
• Troubleshot complex production issues across databases, backend services, and infrastructure layers.
• Applied distributed systems principles inspired by blockchain and crypto architectures to build reliable, low-latency production systems.
• Actively shaped AI-facing system architecture, including data pipelines, model-serving integrations, and infrastructure patterns supporting ML training, inference, and observability at scale.

A set of developer, security, and identity infrastructure products supporting application testing, malware protection, and decentralized identity management. The solutions enabled device simulation for Windows and Android development, strengthened security through telemetry-driven anti-malware capabilities, and provided scalable, reliable identity management with a strong focus on data integrity and secure system design.

• Enhanced QEMU and Android emulators with advanced capabilities, including multitouch support and improved device simulation.
• Enabled global engineering teams to test and develop Windows and Android applications without relying on physical devices.
• Streamlined development and testing workflows, improving productivity and consistency across distributed teams.
• Managed and supported components of the Windows Anti-Malware Core Engine, focusing on system resilience, reliability, and correctness.
• Integrated telemetry-driven features to collect and analyze runtime data, supporting improved threat calibration and response.
• Led security mitigation initiatives by analyzing real-world telemetry and gradually disabling legacy Windows security features based on data-driven decisions.
• Led the design and architecture of a Decentralized Identity Management System (DIMS), focusing on secure, scalable, and reliable system design.
• Built a highly available backend infrastructure using Golang and PostgreSQL, emphasizing data integrity, transactional consistency, and high throughput.
• Designed and implemented Solidity smart contracts for asset issuance and lifecycle management, validated through automated testing and deployment pipelines.
• Integrated Proof-of-Stake and Byzantine Fault Tolerance mechanisms, applying distributed systems principles such as fault tolerance and correctness.
• Applied cryptographic techniques including ECDSA, SHA-256, and Zero-Knowledge Proofs to ensure data integrity and privacy-preserving system behavior.
• Conducted load and stress testing to validate system performance under high-load scenarios and monitored system health using Prometheus and Grafana.
• Collaborated with cryptographers, backend engineers, and systems specialists to align architecture decisions with distributed systems and security best practices.
• Explored quantum-resistant cryptographic approaches as part of forward-looking research initiatives.
• Contributed to system foundations and telemetry pipelines that enabled ML-based threat detection, behavioral analysis, and large-scale security analytics.

A safety-critical automotive calibration platform for airbag systems, supporting crash-test simulation, calibration data management, and dynamic parameter tuning and validation. The product enables reliable development and validation of airbag safety systems, with a strong focus on predictable performance, fault tolerance, data integrity, and production readiness.

• Led the full software development lifecycle and partial project management for critical safety calibration applications, including MAC, MADACADAM 1 & 2, and ADAPT.
• Managed a team of 4 engineers, ensuring delivery of high-performance, reliable software used in vehicle safety systems for real-time airbag calibration.
• Designed and implemented core functionalities using C++ and C# with WPF to ensure high performance and low-latency processing.
• Optimized software architecture to handle large-scale data processing, ensuring fault tolerance and resilience under intensive workloads.
• Built simulation systems to process and analyze large datasets, ensuring predictable performance across varying load profiles.
• Created mathematical signal models for dynamic parameter adjustments, allowing precise tuning and validation of airbag safety systems.
• Architected systems that simulated crash-test scenarios with high fault tolerance and failover mechanisms.
• Ensured scalability and correctness trade-offs while processing massive volumes of simulation data.
• Implemented cryptographic algorithms to ensure data security during simulation runs and configuration exports.
• Integrated security protocols for validating simulation data integrity and preventing unauthorized access.
• Managed a team of 4 engineers, establishing Agile methodologies for iterative development and continuous feedback.
• Fostered cross-team collaboration to address system-level challenges effectively.
• Developed robust CI/CD pipelines for automated deployment and testing.
• Implemented real-time monitoring tools to track software performance during simulation and crash-test execution.