Emir – Python, AWS, React

A platform designed to serve as a central hub for AI agents and intelligent systems. The platform primarily enables structured communication, collaboration, and coordinated execution across multiple agents, tools, and networks.

• Architected and led the development of a multi-agent orchestration platform supporting multi-LLM execution (5+ model providers), real-time agent coordination, and onchain agent identity via ERC-8004, forming the core infrastructure of the platform's protocol;
• Designed and implemented an ERC-8004–compliant agent lifecycle and identity system, enabling 100+ registered agents in closed beta to be verifiably created, managed, and coordinated onchain while keeping execution logic and sensitive data offchain;
• Built real-time agent-to-agent communication and task execution pipelines capable of handling thousands of agent interactions per day with low-latency state updates and full observability;
• Integrated 5+ external APIs and tooling frameworks (LLMs, memory layers, automation tools) into a unified orchestration layer, allowing agents to dynamically select models, tools, and execution paths based on task context;
• Established scalable backend architecture and CI/CD pipelines, supporting weekly production releases and protocol-level upgrades with minimal downtime across a distributed engineering team of 4 core contributors.

It's a platform designed to serve as a premier hub in the startup ecosystem. The platform primarily fosters meaningful connections between startups, venture capitalists, and angel investors.

• Architected and oversaw the development of the back-end infrastructure, ensuring scalable and efficient operations;
• Configured real-time notifications for various events like funding rounds, exits, or important news;
• Led the team in the implementation of an AI-powered recommendation engine, increasing user engagement by 30%;
• Implemented agile methodologies and CI/CD pipelines;
• Generated an LLM model using Langchain and OpenAI to process large amounts of financial data, including investments, rounds, companies, and more;
• Fostered relationships with venture capitalists and angel investors, resulting in a 25% increase in platform investments.

It's a platform designed to ensure only safe, high-quality, and relevant data is fed into language models. The platform's labeling technology allows companies to easily:

1. Auto-generate metadata describing the contents of their data
2. Find & remove sensitive information
3. Control what data can be accessed by which user

• Architected and oversaw the development of the back-end infrastructure, ensuring scalable and efficient operations;
• Led the team in the implementation of an evidence and lineage system for the LLM RAG system, leading to the successful signings of multiple clients;
• Implemented agile methodologies and CI/CD pipelines;
• Generated an LLM model using OpenAI and Azure to process large amounts of document data;
• Rewrote the chatbot use case to use structured and unstructured data in a hybrid engine.

The project is focused on developing advanced software solutions for autonomous vehicle systems.

• Took the lead in designing and deploying complex software solutions for autonomous vehicle systems, enhancing operational efficiency and reliability;
• Crafted a software tooling kit, including a CLI, that served as the backbone for the Engineering division's development activities;
• Revamped the CI/CD pipeline, automating builds and artifact management to streamline the development process.

It's a transport and logistics company with two major projects. The first one is designed to streamline and manage the operations of one of Europe's largest shipping companies. The second one - to automate the transportation of goods between ports and logistics centers.

• Excelled in architecting scalable and robust systems;
• Contributed to the Phoenix team, focusing on central bookings, customs integration, and third-party service integration;
• Took full responsibility for tasks from initial design to deployment and ongoing support, ensuring high customer satisfaction and project success;
• Created front-ends for services that customers could use to track their data;
• Adopted Agile Scrum methodologies, utilizing Azure DevOps for backlog management and CI/CD pipelines.

It's a diverse range of software solutions, including a Data Management Platform, a Multi-Channel Data System, and specialized services like License Plate Detection and Loyalty Programs.

• Oversaw the development of a Data Management Platform and Multi-Channel Data System;
• Excelled in team leadership, guiding the transition to microservices;
• Utilized React to create a dynamic front-end where each module of the MDM could be efficiently viewed and processed;
• Implemented ETL and big data visualization;
• Utilized Kafka for data integration services;
• Communicated with customers to provide a dynamic user flow for their needs.

It's the main product within the Energy Management sector of Siemens. The system provided Supervisory Control and Data Acquisition and Human-Machine Interface capabilities.

• Developed custom integration services for diverse clients;
• Built reporting and team collaboration tools for outage tracking and short circuit calculations;
• Created a GIS platform for monitoring and administration of utility systems.