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Mid-level AI engineering role in Bengaluru, notable employer, and broad AI/data skillset draws strong applicant competition.
Medium because core AI/data engineering skills transfer, but enterprise data governance and MDM knowledge is domain-specific.
High due to explicit 5+ years requirement and extensive mandatory AI, data pipeline, and governance skills.
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Own the design and implementation of production-grade data pipelines ingesting, normalizing, and synchronizing structured and unstructured enterprise data from multiple sources.
Build and maintain secure, governed MCP/API tools and retrieval systems ensuring reliable, traceable, and access-controlled AI context and data delivery.
Develop evaluation harnesses, operational checks, and human-in-the-loop workflows for AI data quality, retrieval accuracy, security, and governance.
5+ years of experience in software, backend, data platform, or AI engineering building production data systems or AI-enabled systems.
Proficiency in Python and/or TypeScript/Node.js with experience designing APIs, services, async jobs, and integrations.
Hands-on experience with data ingestion, transformation, synchronization, and operational data pipelines.
Practical knowledge of RAG/retrieval systems, embeddings, vector stores, source provenance, and enterprise identity/access controls (OAuth/SSO, RBAC/ABAC).
Experienced engineer focused on building backend data infrastructure and governed AI context systems rather than front-end/UI development.
Skilled in creating secure, scalable APIs and tools that support enterprise AI workflows with strong emphasis on data governance and access control.
Able to translate complex enterprise workflows into durable, governed AI capabilities working collaboratively with cross-functional stakeholders.