AI Data Engineer

Min 12+ into IT Exp required with min 2 to 4 years to AI Agents across cloud, MCP,

• Design and build scalable data pipelines for AI agents across cloud platforms
• Create and maintain agent‑ready data models, schemas, and data contracts
• Build and operate vector data pipelines (data prep, chunking, embeddings, indexing, re‑indexing)
• Integrate structured, semi‑structured, and unstructured data sources for agent consumption
• Develop MCP (Model Context Protocol) data adapters/connectors for databases, APIs, SaaS, files, and streams
• Define standard MCP request/response schemas and transformation logic
• Integrate MCPs with the MCP gateway (auth, routing, throttling, observability)
• Build CI/CD pipelines for MCP build, test, deployment, and rollback
• Implement CI/CD pipelines for data pipelines, datasets, and vector stores
• Design and operate real‑time streaming pipelines (event ingestion, enrichment, aggregation)
• Build batch + streaming hybrid architectures for historical and real‑time context
• Develop and maintain certified data connectors for Low‑Code / No‑Code platforms
• Standardize enterprise data models for reuse by agents and citizen developers
• Manage secure data access using RBAC, managed identities, secrets, and tokenization
• Monitor data quality, drift, and freshness impacting agent behavior
• Implement data observability and lineage tracking across pipelines and MCPs
• Enforce data governance, classification, and compliance controls
• Optimize data performance, latency, and cost for agent workloads
• Experience developing these using AWS cloud services and open source