Overview: Portfolio of 5 internal platforms used by 3,000+ software engineers, as well as executives and board members. ● Marketplace is a self-service provisioning platform that enables engineers to provision software components on virtual machines and Kubernetes clusters with a single click. Supported components include databases, monitoring tools, and internal services. ● DORA Metrics and DORA Capabilities are products that collect and analyze engineering performance metrics across delivery and reliability dimensions. ● Tech Radar is a platform for tracking technology adoption across engineering teams. It visualizes technology adoption, tracks lifecycle status, and provides usage recommendations. ● Research is an internal survey and analytics platform used to collect feedback and analyze results. The platform is used for employee engagement surveys and customer satisfaction research. Key Contributions: ● Provided technical leadership across 5 engineering teams supporting a portfolio of internal platforms used by 3,000+ engineers. ● Established the architectural direction for internal developer platforms, guiding technology choices, scalability targets, and platform evolution across multiple product teams. ● Influenced roadmap decisions across engineering leadership. ● Oversaw development of Python microservices and drove product strategy and technical direction. Fostered knowledge sharing across the organization's Python and DevOps communities. ● Mentored senior engineers and tech leads. ● Led hiring and interview processes for several teams. Achievements: ● Defined the architectural vision and technical strategy for a portfolio of 5 internal platforms serving 3,000+ engineers. ● Established architecture review processes, service design standards, and operational readiness requirements adopted across 5 engineering teams. ● Influenced technical decision-making across engineering leadership, product stakeholders, and platform teams without direct reporting authority. ● Led cross-team architecture discussions and resolved competing technical priorities across platform initiatives. Databases & Technologies: ● PostgreSQL, Redis, Elasticsearch. ● Python 3 (asyncio, FastAPI, SQLAlchemy + Alembic, Poetry, isort, mypy, ruff), SQL, RabbitMQ, Ansible, GitLab, Docker, Kubernetes, Artifactory.

Overview: ● FedEx Shipment System: designed and implemented a platform for tracking and managing cross-border shipments between the USA and Canada. ● Legacy Modernization Program: led the migration of legacy systems written in RPG and COBOL to modern Python. ● Critical Event Management Platform: delivered solutions used by more than 50,000 customers worldwide. Key Contributions: ● Built Python microservices following an API-first approach and exposing REST APIs, while designing software architecture and implementing unit, integration, and end-to-end tests. ● Gathered requirements from internal and external stakeholders, conducted demos, developed proof-of-concepts (PoCs), performed business analysis, and clarified functional and system requirements. ● Led project teams of 4–8 engineers, ensuring on-time delivery and adherence to high-quality standards. Achievements: ● Led modernization of monolithic systems into cloud-native, event-driven architectures. ● Migrated a mission-critical shipment platform from an RPG monolith to Python microservices, enabling independent deployment and scaling of business capabilities. ● Delivered a Change Data Capture (CDC) solution using SQL triggers and IBM i data queues. ● Mentored 10+ engineers in hexagonal architecture principles and service design practices. Databases & Technologies: ● PostgreSQL, Redis, DB2 for IBM i. ● AWS, Python 3 (asyncio, FastAPI, SQLAlchemy + Alembic, Poetry, Black, isort, mypy), SQL, RabbitMQ, Docker, Kubernetes, Helm, Bash, RPG, CL, IBM MQ.

Overview: ● Developed the core banking system based on the Misys platform, a widely adopted core banking solution used by hundreds of financial institutions worldwide. Key Contributions: ● Engineered cash management, lending, deposit processing, and SWIFT messaging capabilities for the core banking system, handling billions of dollars in daily transactions and supporting banking operations for millions of customers. ● Organized and led regular code reviews and implemented unit tests to ensure high code quality and reliability. Managed the release process by defining feature sets, coordinating with stakeholders, and performing detailed release planning. Achievements: ● Promoted from Software Engineer to Lead Software Engineer over 3 years. ● Developed a C++ ORM library for IBM i files (PF, LF, DSPF, PRTF), significantly improving developer productivity. ● Configured and optimized CI/CD pipelines, improving deployment efficiency and system reliability. ● Designed and implemented two RPG code testing methodologies using JUnit and GoogleTest, substantially improving testing accuracy and coverage. Databases & Technologies: ● DB2 for IBM i. ● SQL, C, C++ (STL, GoogleTest), RPG, CL, Bash, PowerShell, IBM MQ.

Overview: ● Multi-exchange trading infrastructure supporting market data, risk controls, analytics, and capital management for systematic trading strategies. Key platform services include: ● PyCore is a legacy monolithic service that powers several critical trading workflows, including transfers, balancing, exchange integrations, funding fee collection, and operational automation. It acts as an integration layer between internal trading components and external exchanges. ● Data Pipelines is a data ingestion and analytics platform. It ingests trading events from Kafka and stores them in ClickHouse, making datasets such as positions, exposures, leverage levels, funding fees, funding rates, orders, RFQs, symbology changes, and theoretical prices available for historical analysis and backtesting. ● Safeguards is a standalone service built with FastAPI responsible for monitoring trading instances and validating operational safeguards. It consumes configuration and state changes from Kafka, runs automated checks, and provides real-time status updates to trading systems via WebSockets. Key Contributions: ● Developed Kafka-based data ingestion and ClickHouse-backed analytics pipelines. ● Designed and implemented market data infrastructure ingesting real-time exchange feeds from Binance, Kraken, Hyperliquid and Huobi. ● Refactored and extracted legacy components into standalone services with modern CI/CD and Kubernetes-based deployments. ● Implemented and supported event-driven services using Kafka, including real-time WebSocket delivery. ● Designed, implemented, and maintained backend services, shared libraries, and data pipelines within a multi-exchange trading platform. ● Collaborated with traders, quants, and infrastructure engineers to clarify data semantics, correctness requirements, and operational constraints. ● Maintained and enhanced production systems, including on-call participation, incident investigation, and reliability engineering initiatives. Achievements: ● Built the Safeguards service from scratch, monitoring 100+ trading instances through an event-driven architecture leveraging log-compacted Kafka topics and real-time WebSocket updates. ● Diagnosed and resolved critical performance and reliability issues, including memory leaks, CPU bottlenecks, async scheduling defects, and socket handling problems, reducing memory consumption by ~60% and service restart frequency by ~80%, significantly improving production stability. ● Extracted and rebuilt multiple services from a legacy monolith into independently deployable systems, reducing deployment risk and improving operational visibility through GitOps and observability tooling. ● Expanded a Kafka-to-ClickHouse analytics platform processing tens of millions of trading events daily with sub-second ingestion latency and high availability requirements, enabling historical analysis, backtesting, and P&L reporting across critical trading datasets. ● Corrected high-impact issues in timestamp semantics, schemas, and ingestion logic, improving the accuracy of historical analytics and trading-performance reporting. ● Reduced manual operational checks from hours to minutes through automated validation workflows (pair discovery, configuration validation, quota monitoring, production checks). ● Delivered market data and funding integrations for 4 exchanges (Binance, Huobi, Kraken, Hyperliquid), handling exchange-specific semantics, rate limits, and payload constraints. ● Improved transfer and capital allocation workflows across exchanges, increasing capital mobility and operational resilience. Databases & Technologies: ● PostgreSQL, Redis, ClickHouse. ● AWS, Python 3 (asyncio, Django, FastAPI, SQLAlchemy + Alembic, Poetry, isort, mypy, ruff), SQL, Kafka, GitLab, Docker, Argo CD, Kubernetes, Helm, Prometheus, Grafana, WebSockets.