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Strong employer brand, metro location, broad AI/data skillset, and visible fullstack title increase candidate competition.
Core AI/data engineering skills are transferable, but regulated healthcare and compliance needs increase domain specificity.
Mandatory 7+ years plus extensive required AI/data engineering, cloud, orchestration, and infra tooling enforces strict filters.
Design and implement scalable, high-performance data infrastructure and pipelines to support AI/GenAI applications, including vector and graph databases in cloud-native environments.
Collaborate within autonomous agile teams to integrate LLMs and build production-ready generative AI solutions focusing on real-time performance, robustness, and compliance.
Ensure data governance, security, and operational reliability through monitoring, alerting, and adherence to regulatory standards in a highly regulated healthcare setting.
7+ years of experience in data engineering, preferably supporting AI/ML applications.
Proficient in Python programming and advanced SQL for production-grade code and complex queries.
Hands-on experience with ETL/ELT data pipelines, Snowflake, orchestration tools (like Airflow), vector and graph databases, and cloud platforms (AWS or Azure).
Bachelor's degree or higher in Computer Science, Data Engineering, or related field; located in Hyderabad, India with work hours overlapping CET.
Experienced in architecting scalable, fault-tolerant data pipelines and managing both structured and unstructured datasets for AI systems, including RAG and fine-tuning workflows.
Comfortable working in small, autonomous teams applying agentic software development lifecycles using AI coding assistants and conducting rigorous code reviews.
Strong understanding of data security, governance, software engineering best practices, and ethical AI deployment within regulated industries.