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 Rubiscape’s differentiation as a unified
Decision Intelligence Platform with 8 international innovation patents.
· Design and
operate Rubiscape’s 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 platform’s 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.
· 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.
Rubiscape is India’s 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.
RequirementsRequirements
· 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.



