Senior AI Architect / Data Scientist REMOTE - USA
We are seeking an Onshore Senior AI Architect / Data Scientist to design and scale intelligent, multi-modal Al solutions on Databricks using GenAI and modern orchestration frameworks. Please share the profiles by the end of this year(12/31) and these profiles will be reviewed in Jan 2026. Below are high level details of this role.
Details: The role demands strong Databricks expertise, GenAI integration skills( hands on) and architecture-level design thinking. The selected candidate will play a key role in architecting and expanding our next-generation intelligence platform across multiple use cases under the Global Brand Protection program.
Core Use Cases Columbo: Natural Language to SQL search over Databricks data, including fuzzy matching and unstructured text handling. Sales Anomaly Detection: Isolation-Forest-based anomaly detection on sales data. Counterfeit Image Detection: ViT-based image authenticity classification.
Key Responsibilities Provide technical leadership across AI architecture model integration, and delivery. Architect end-to-end AI pipelines using Databricks (Delta, Unity Catalog, MLflow, Model Serving). Integrate GenAI platforms (Mosaic AI, Genie, Azure OpenAI) and orchestrate them via an MCP server for NL SQL and conversational intelligence. Implement governed, cost-optimized MLOps pipelines with retraining, lineage, and observability. Build multi-agent architectures combining text, tabular, and image models. Enforce role-based security and governance through Unity Catalog. Collaborate with UI (React) teams to integrate model outputs in Databricks web apps. Lead feedback-driven model improvements and cross-functional mentoring.
Core Skills Databricks Platform: SQL Warehouse, Unity Catalog, MLflow, Model Serving, OCR. GenAI Tools: Mosaic AI, Genie, Azure OpenAI, LangChain, Vector Search, MCP Server for orchestrating AI tools and context. ML Techniques: Isolation Forest, PSI/KSI drift detection, model retraining. Vision Models: ViT, Grad-CAM, explainability methods. Data Engineering: Spark, Python, Delta Lake, REST APIs. Governance & Security: RBAC, lineage, masking, compliance policies. Soft Skills: Architecture design, stakeholder alignment, communication.
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