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Data Systems Rust Developers

Designed MLS group-state features and bidirectional streaming transport for secure messaging, including ordered delivery, heartbeats, reconnects, external invites, and per-field permissions. Reduced 100-device group-invite storage from 8 MB to 200 KB and reduced full-group database loading from 13 reads to one.

• Migrated core product infrastructure into Rust
• Built FFI boundaries for untrusted drivers
• Enabled PostgreSQL through asynchronous database traits
• Shipped four protocol improvement proposals

Engineered high-performance data processing pipelines using Scala and Rust, focusing on real-time analytics. Designed and maintained distributed systems for large-scale data ingestion and processing.

• Built microservices architecture using Go and Java
• Integrated TypeScript for front-end data visualization
• Optimized C++ algorithms for data compression

Architected large-scale, multi-agent AI systems with real-time decision-making capabilities. Designed data systems leveraging GraphRAG for enhanced relational data retrieval and processing.

• Implemented LangChain for natural language processing tasks
• Developed scalable AI solutions on VertexAI platform
• Pioneered multi-agent orchestration techniques

Engineered quantitative trading algorithms using Python and Rust, optimizing execution on cloud platforms. Automated deployment pipelines with Kubernetes for seamless CI/CD.

• Integrated AWS for cloud-based computation
• Utilized Docker for containerized environments
• Implemented robust CI/CD with GitLab

Architected distributed systems with a focus on scalability and high availability. Applied domain-driven design principles to streamline AI/ML application development.

• Led system analysis for enterprise-level applications
• Implemented event-driven architectures with Rust
• Optimized machine learning pipelines for performance

Migrates core components of the Redis RediSearch C query engine to Rust across a performance-sensitive C/Rust boundary while preserving behavior and throughput. Has also co-authored incremental C-to-Rust migration training material and built production Rust services integrating Kafka, backend systems, and infrastructure.

• Security issue discovery in search infrastructure
• Rust FFI and C ABI maintenance
• WebAssembly component development
• Axum and Tokio service implementation

Engineered quantitative models using Rust and Python for financial analytics. Managed cloud-based data processing on AWS and Azure, optimizing cost and efficiency.

• Developed API integrations for trading platforms
• Utilized Google Cloud for scalable data storage
• Created dashboards for real-time financial metrics

Architected blockchain solutions for both EVM and non-EVM platforms, focusing on data integrity and scalability. Designed complex algorithms and data structures for distributed systems.

• Developed consensus protocols for blockchain networks
• Optimized system design for high throughput
• Implemented cryptographic algorithms for security
• Led cross-functional teams in blockchain projects

Engineered cross-platform software systems with Rust and Go for distributed environments. Optimized x86 assembler code for performance-critical applications. Developed real-time data processing solutions for cloud services.

• Engineered cross-platform systems with Rust and Go
• Optimized x86 assembler for performance
• Developed real-time data processing solutions

Led development of distributed systems using NodeJs and Rust for real-time data processing. Implemented Kafka for event-driven architectures to handle high-throughput data streams. Utilized Redis for caching and fast data access.

• Integrated GitlabCI for automated testing and deployments
• Developed monitoring solutions with Kibana
• Optimized data flow with advanced queuing techniques

Built backend and data platforms using Python, Rust, PostgreSQL, Airflow, and CDC synchronization, including an enterprise warehouse with dimensional modeling and SCD Type 2 history. Implements asynchronous services with epoll-based I/O, binary protocol parsing, database query planning, and safeguards for financially sensitive payout workflows.

• RBAC-protected operational application for 80 users
• PostgreSQL B-tree and query-planning knowledge
• AWS Lambda and S3 deployments
• Power BI finance and operations analytics

Designed and implemented distributed systems for a high-traffic e-commerce platform using Rust and Scala. Optimized database query performance in SQL to handle millions of transactions per day.

• Built a real-time analytics pipeline in Python
• Developed microservices architecture with Java
• Automated CI/CD pipelines using Bash scripts

Architected Rust data-processing services using Apache DataFusion for large structured and unstructured datasets, with cloud-native orchestration through Argo Workflows. Also built Rust APIs and integration services over relational, graph, and vector databases, covering deployment, observability, and production monitoring.

• Functional-programming patterns in backend architecture
• Scala and Python data-pipeline integration
• Performance-critical Rust component adoption
• Production service lifecycle instrumentation

Built a browser-based photorealistic 3D product visualization platform with a custom rendering engine and an embeddable JavaScript SDK. Architected distributed GPU job processing that parallelizes rendering across worker machines and supports configurable product rules, pricing, and interaction constraints.

• WebGL, OpenGL, and Vulkan rendering pipelines
• Rust async services using Tokio and Axum
• Kafka, RabbitMQ, Redis, and Valkey integration
• Browser-based WebSocket and GraphQL interfaces