AI Platform Engineer

":" About the Role

The AI Platform Engineer at Rubiscape is the architect of the infrastructure layer that powers RubiAI our agentic AI copilot and the shared AI services consumed by all six studios. You will build the foundations: LLM gateway, RAG orchestration layer, prompt management system, vector store integrations, and the real-time inference bus that serves enterprise customers across SaaS, BYOC, and air-gap topologies. This is a high-ownership role at the core of Rubiscapes differentiation as a unified Decision Intelligence Platform with 8 international innovation patents.

Key Responsibilities

Design and operate Rubiscapes LLM gateway: request routing, model failover, token budgeting, cost attribution, and rate-limit enforcement across multiple LLM providers and self-hosted models.

Build and maintain the RAG pipeline infrastructure document chunking, embedding generation, vector store management (Weaviate/Qdrant/pgvector), and retrieval orchestration using LangChain or LlamaIndex.

Own the prompt management system: versioning, A/B evaluation, regression testing, and deployment of prompt templates used across RubiAI and studio co-pilots.

Architect low-latency inference APIs that serve both synchronous (sub-200ms) and streaming (SSE/WebSocket) AI responses to the Rubiscape front-end and third-party integrations.

Implement guardrails, content filtering, and PII redaction layers required for regulated-sector AI deployments in BFSI, healthcare, and government.

Work with the MLOps team to integrate fine-tuned and quantised open-source models (Llama, Mistral, Phi) into the platforms model registry and serving infrastructure.

Establish platform-wide observability: trace AI requests end-to-end from user query through retrieval, LLM call, and response synthesis using OpenTelemetry and internal dashboards.
Nice to Have

Experience building agentic AI systems with tool use, multi-step planning, and memory management.

Knowledge of model compression techniques (quantisation, distillation, speculative decoding) for on-premises or edge AI deployment.

Exposure to enterprise AI governance frameworks and responsible AI principles relevant to regulated sectors.

Contribution to open-source LLM or RAG projects.

About Rubiscape

Rubiscape is Indias leading Decision Intelligence Platform, unifying data engineering, BI, machine learning, and agentic AI in a single governed platform. Built in Pune and trusted by Fortune 500 enterprises across BFSI, manufacturing, healthcare, and government. 8 international innovation patents. 10 Industry-Academia Labs COEs. From BI to AI One Platform. Every Decision.

Requirements Requirements

4+ years in platform, infrastructure, or backend engineering with at least 2 years focused on AI/LLM systems in production.

Deep hands-on experience with LangChain or LlamaIndex for RAG pipeline construction and agentic workflow orchestration.

Proficiency in Python for high-performance backend services and familiarity with async frameworks (FastAPI, asyncio).

Practical experience with vector databases (Weaviate, Qdrant, Pinecone, or pgvector) at production query volumes.

Strong understanding of LLM deployment options: OpenAI/Anthropic API, Azure OpenAI, vLLM, Ollama, and quantised model inference.

Experience designing multi-tenant AI services with security isolation, audit logging, and usage metering.

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