5+ years of software or data engineering experience, or equivalent significant experience building systems with coding in languages & frameworks including, but not limited to, Python, Spring Boot, .NET, with demonstrated ownership through implementation and support.
Strong backend programming and systems engineering skills, including designing maintainable services, modular components, APIs, and automated tests.
Deep experience designing, building, and operating data generation, ETL, and distributed data-processing workflows, including creating, scaling, and maintaining cloud-based pipelines.
Strong working understanding of large language models (LLMs), including their capabilities, limitations, common failure modes, and the role of data quality, prompting, evaluation, and model behavior in AI-powered systems.
Working knowledge of orchestration, concurrency, asynchronous execution, streaming or event-driven architectures, and recovery from failures.
Strong knowledge of large-scale data storage, modeling, and retrieval, including partitioning, indexing, access patterns, and trade-offs among storage approaches.
Strong quantitative analytical and troubleshooting skills, with the ability to validate data and system behavior, interpret performance measurements, and make evidence-based engineering decisions.
Practical cloud engineering experience
