Company Description Proximal Cloud is the creator of the world’s first Sovereign Enterprise AI Platform, designed to combine public cloud agility with the security and control of private environments. Using a proprietary Hub-and-Spoke architecture, Proximal brings compute to enterprise data so it never leaves the organization’s security perimeter, whether on-premise, in private cloud, or at the edge.

The platform includes Proximal Unity™, an AI-in-a-Box solution delivering high-performance inference at lower total cost of ownership, and Crania™, an intelligence engine that turns complex data into forward-looking insights while addressing issues such as context decay and hallucinations. With strong sovereignty and compliance capabilities (SOC 2, HIPAA, GDPR ready), Proximal helps enterprises operationalize AI at scale. In partnership with UC San Diego and AMD, the company is driving impact across education, healthcare, and precision agriculture through initiatives such as the TAU Neocloud.

Role Description The Data Platform Architecture & AI Integration Consultant will design, implement, and optimize data platform architectures that support Proximal’s sovereign AI solutions for enterprise clients. This full-time, hybrid role is based in Bengaluru, with flexibility for partial work-from-home, and involves close collaboration with customer stakeholders, product teams, and engineering to translate business requirements into scalable, secure data and AI integration patterns.

Day-to-day responsibilities include assessing client data landscapes, defining integration strategies, configuring and orchestrating data flows, and ensuring interoperability between existing systems and Proximal’s platform. The consultant will guide clients on best practices for data sovereignty, governance, and performance, troubleshoot complex integration issues, and contribute to solution proposals, technical documentation, and implementation roadmaps. The role also includes conducting workshops, providing advisory support on AI/ML enablement,



and continuously improving architecture blueprints based on emerging technologies and client feedback.

Here is a high-engagement, "viral-style" LinkedIn post tailored to attract elite candidates. It uses algorithm-friendly formatting (short, scannable lines, explicit hooks, strong white space, and high readability).

We’re building the AI-ready research engine of the future.

Most data catalogs (like CKAN) are great systems of record. But they weren't built for modern AI/ML workflows.

We're fixing that. ?️

We’re looking for a Data Platform Architecture & AI Integration Consultant to bridge the gap between our National Data Platform (NDP) and Deep Lake.

This isn't a "sit back and maintain" role. You will design the blueprint, build write-back pipelines, and hand over a fully versioned AI retrieval layer to top-tier academic teams.

? The Setup

- Role: Lead AI Data Platform Consultant
- Engagement: 8–10 Weeks (Phased)
- Format: Remote / Phased Consulting Enablement

? What You’ll Own

1. The Blueprint: Design identity-aware (CILogon/OIDC), federated integration patterns between CKAN and Deep Lake.
2. The Pipelines: Build automated chunking, embedding, and write-back pipelines with full dataset versioning.
3. The Retrieval Layer: Enable RAG-ready semantic search with >95% provenance back to NDP source metadata.
4. Knowledge Transfer: Deliver Jupyter tutorials and runbooks so internal teams and faculty can run experiments independently.

? What We’re Looking For

- Proven experience with CKAN (or distributed data catalogs).
- Deep expertise in Deep Lake, DVC, or LakeFS dataset versioning.
- Comfort with multimodal research data (text, tabular, geospatial, images).
- Hands-on mastery of Kubernetes, Docker, and JupyterHub workflows.
- Clear communication skills to turn complex infrastructure into student-friendly documentation.

⏱️ The Timeline

- Weeks 1–2: Discovery, Security, & Blueprint Design
- Weeks 3–5: Build Ingestion & Write-Back Pipelines (Target: ≥3 core datasets)
- Weeks 6–8: RAG Workflows, Semantic Search & Provenance API
- Weeks 9–10: Handover, Enablement, & Educational Runbooks

📌 Data Platform Architecture & AI Integration Consultant (Bengaluru)
🏢 Proximal Cloud
📍 Bengaluru