Aram Leblebjian

Grid Dynamics is a global provider of technology consulting and enterprise-scale digital transformation solutions. The role focuses on delivering Level 2 technical support for a leading integrated development environment (IDE) company. The position centers on reproducing and investigating complex issues in Java projects, analyzing build environments, and working closely with development teams to provide technical insights. It also involves deep technical troubleshooting such as log analysis, CPU/memory diagnostics, and investigation of networking-related issues. Responsibilities: * Reproducing and investigating user-reported issues in Java applications using Maven, Gradle, and IDE tooling. * Analyzing logs, CPU snapshots, memory reports, and networking configurations to identify performance and stability problems. * Troubleshooting build and runtime issues across diverse environments to isolate root causes. * Collaborating with development teams to validate bugs, suggest fixes, and ensure accurate escalations. * Creating and maintaining technical articles and documentation to guide users and internal teams. * Gathering and structuring user feedback to support new feature development. * Tracking recurring issues and providing detailed case reports to drive long-term product improvements.

This position supports the delivery of undergraduate-level and graduate-level coursework in database systems. The role involves assisting students in understanding core database principles and guiding them through practical exercises and assignments. The objective is to reinforce theoretical knowledge with hands-on support and ensure student success through academic mentoring. Responsibilities: * Guiding students through the course load by holding weekly problem-solving sessions and office hours. * Assisting students with topics such as relational algebra, normalization, MySQL, and database design. * Supporting the primary instructor in preparing and explaining course material. * Assisting in the creation and grading of exams and assignments. * Offering constructive feedback to help students optimize their database solutions and strengthen their understanding.

This position supports the delivery of undergraduate-level and graduate-level coursework in object-oriented programming using Java. The position focuses on reinforcing foundational programming concepts through practical application, student mentoring, and academic support. The objective is to help students build strong coding skills, understand object-oriented design, and apply best practices in software development. Responsibilities: * Conducting weekly coding sessions and problem-solving workshops focused on Java and OOP principles. * Guiding students through assignments and debugging during labs and office hours. * Supporting the evaluation and grading of programming assignments. * Providing feedback to help students improve code structure, logic, and best practices.

SuperAnnotate provides a data annotation and MLOps platform for computer vision, LLM, and multimodal AI teams. The role supports clients in deploying, scaling, and customizing their data pipelines and integrations. The goal of the position is to ensure customer success by enabling smooth data operations and solving technical blockers related to platform usage and integration. Responsibilities: * Designing and deploying pipelines to integrate external APIs with SuperAnnotate's platform. * Troubleshooting technical issues related to data processing, platform behavior, and user requests. * Supporting customers with advanced technical inquiries and ensuring timely resolution. * Collaborating with product and engineering teams to report issues and suggest improvements. * Ensuring data integrity and automation across client projects.

This internship focused on applied research and development in large language models (LLMs) and conversational AI. The main objective was to design, implement, and evaluate intelligent agents capable of maintaining dynamic, multi-persona conversations in natural language, with a focus on voice interaction and prompt-based logic. Responsibilities: * Developing a voice-based conversational bot using Python and the Autogen framework. * Refining prompts to shape the behavior and tone of LLM-driven agents. * Designing and testing multiple agent personas for diverse interaction scenarios. * Building evaluation matrices to measure conversation quality, responsiveness, and consistency. * Researching and implementing strategies to improve agent coordination and dialog flow.

This role involved providing technical and domain-specific support to ServiceTitan users in the areas of accounting, invoicing, inventory management, and pricebook configuration. The goal was to help customers resolve platform-related issues and optimize their financial workflows through accurate guidance and in-depth troubleshooting. Responsibilities: * Providing expert-level support on accounting workflows, including invoice adjustments, General Ledger configuration, and transaction troubleshooting. * Assisting users in managing inventory systems and utilizing the pricebook for product and service structuring. * Resolving customer inquiries through ticketing systems and live communication (chat and phone), ensuring timely and effective solutions. * Identifying root causes of complex issues and collaborating with internal teams for resolution and escalation. * Delivering product education and feature usage tips to enhance customer adoption and satisfaction. * Documenting troubleshooting steps and contributing to support knowledge base articles.

This research internship focused on the study and implementation of Generative Adversarial Networks (GANs) and their variants, with the goal of exploring advanced techniques for improving generative model stability and output quality. The position emphasized hands-on model development, evaluation, and academic analysis. Responsibilities: * Conducting literature reviews on GAN architectures, including WGAN, CGAN, and DCGAN. * Implementing and training GAN models in Python to generate synthetic image data. * Analyzing model performance using custom metrics. * Researching methods to stabilize training and improve convergence in generative models. * Participating in team discussions on research direction, model tuning, and findings.