vvilli4m

Quality Engineer specialized in non-custodial Web3 wallets and on-chain transaction systems, with 3+ years of hands-on experience validating irreversible transaction flows in production environments.

Focuses on testing real wallet behavior rather than theoretical cases: transaction construction and signing (software and hardware wallets), RPC calls, routing logic, gas and fee parameters, and final on-chain outcomes verified through blockchain explorers. Daily testing spans EVM and non-EVM networks in multichain contexts (35+ natively supported chains and thousands of configurable networks), including chain-specific constraints and edge cases.

Core scope includes account and network management, swaps (routing, slippage, custom recipients, gas abstraction), dApp connections (sign, approve, revoke), staking, liquidity providing, NFT flows, and fiat on-ramps. Strong attention to user-loss scenarios caused by unsafe defaults, misleading UI, incorrect network states, malicious contracts, phishing patterns, or routing inconsistencies.

Testing is primarily manual and system-oriented, driven by Jira requirements and Figma designs, and executed across browser extensions and mobile applications. Comfortable inspecting RPC payloads, network responses, and console logs, and providing developers with concrete debugging artifacts such as transaction hashes, explorer links, route identifiers, and trace data. Regularly reproduces production issues reported by support and validates fixes across staging and production environments.

Executes already implemented CI test suites (smoke and regression) on the appropriate branches and reviews Allure reports to analyze failures or retests. Uses automation results as input for manual verification and regression checks, without owning test implementation. Contributed to a major non-custodial wallet revamp and rebrand (XDEFI → CTRL), ensuring behavioral correctness, backward compatibility, and alignment between extension and mobile platforms. Works in fully remote Agile/Scrum environments with a strong focus on reliability, reproducibility, and long-term product stability.

Maintains a continuous learning mindset and is open to progressively expanding automation knowledge to better support regression and release validation.