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Schedule Interview NowMy name is Aleksandr M. and I have over 4 years of experience in the tech industry. I specialize in the following technologies: API Testing, Rest Assured, RESTful API, Postman, SQL, etc.. I hold a degree in Master of Computer Applications (MCA), , Master of Business Administration (MBA). Some of the notable projects I’ve worked on include: Mock-based Prompt QA Testing for LLM Agents (LangChain + PyTest), AI-Driven Data Quality Checker with LangChain Integration, LangChain Agent for Smart Contract QA – Crypto QA Framework, Automated Testing of E-Commerce Web Application, Excel dashboard with data map and filters, etc.. I am based in Yerevan, Armenia. I've successfully completed 11 projects while developing at Softaims.
Information integrity and application security are my highest priorities in development. I implement robust validation, encryption, and authorization mechanisms to protect sensitive data and ensure compliance. I am experienced in identifying and mitigating common security vulnerabilities in both new and existing applications.
My work methodology involves rigorous testing—at the unit, integration, and security levels—to guarantee the stability and trustworthiness of the solutions I build. At Softaims, this dedication to security forms the basis for client trust and platform reliability.
I consistently monitor and improve system performance, utilizing metrics to drive optimization efforts. I’m motivated by the challenge of creating ultra-reliable systems that safeguard client assets and user data.
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ServiceTitan
Developed a lightweight framework for validating prompt-based responses of AI agents using Python and PyTest without OpenAI API access. Simulated a mock LLM (MockLLM) to test factual answers, structured JSON output, and Markdown formatting. Tests are designed to ensure response consistency in CI/CD pipelines or low-trust environments. This setup helps validate prompt logic and fallback behavior during early-stage LLM development or offline scenarios.
Developed a backend tool using FastAPI and LangChain to identify data quality issues in Pandas DataFrames. Integrated LLM-based analysis to detect missing, inconsistent, or duplicated values. Implemented automatic Markdown report generation and unit tests with PyTest. This tool helps QA teams analyze data artifacts faster and validate AI output for tabular datasets.
Built a command-line QA tool using LangChain and Python to analyze Ethereum smart contract logs. The agent receives a wallet address or transaction hash and returns test ideas, edge cases, and data inconsistencies. It leverages LLM prompts to simulate common issues in DeFi and NFT contracts. CLI-based interaction and custom tools allow QA insight without full code access. This solution helps blockchain QA teams and auditors to rapidly explore test cases and improve coverage.
Dashboard for analyzing online food sales in Germany for 3 years by city and region. You can clearly see the trends towards a decrease in the share of the southern region and an increase in the share of the north in online sales. Separately, one can see the growth and fall in sales in some of the largest cities in Germany.
Collection of data on books from the online store that are available
Master of Computer Applications (MCA) in Applied Mathematics and Informatics
2012-01-01-2014-01-01
in Faculty of Artificial Intelligence
2020-01-01-2022-01-01
Master of Business Administration (MBA) in Banking and Finance
1992-01-01-1996-01-01