AI Platform Engineer

Posted 6 Hours Ago
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Pune, Maharashtra, IND
In-Office
Mid level
Artificial Intelligence • Software • Analytics • Business Intelligence
The Role
Build and operate Rubiscape’s AI platform infrastructure, including LLM gateways, RAG pipelines, prompt management, vector databases, inference APIs, guardrails, model serving, and observability. Integrate open-source and hosted models across SaaS, BYOC, and air-gapped deployments while supporting multi-tenant security, audit logging, usage metering, and regulated-sector requirements.
Summary Generated by Built In
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 Rubiscape’s differentiation as a unified Decision Intelligence Platform with 8 international innovation patents.

 

Key Responsibilities

·         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.

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 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.



Skills Required

  • 4+ years of experience in platform, infrastructure, or backend engineering
  • At least 2 years focused on AI or 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
  • Familiarity with asynchronous frameworks such as FastAPI and asyncio
  • Practical production experience with vector databases such as Weaviate, Qdrant, Pinecone, or pgvector
  • Strong understanding of LLM deployment options including OpenAI or Anthropic APIs, Azure OpenAI, vLLM, Ollama, and quantised model inference
  • Experience designing multi-tenant AI services with security isolation, audit logging, and usage metering
  • Experience building agentic AI systems with tool use, multi-step planning, and memory management
  • Knowledge of model compression techniques including quantisation, distillation, and speculative decoding
  • Exposure to enterprise AI governance frameworks and responsible AI principles
  • Contribution to open-source LLM or RAG projects
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The Company
30 Employees
Year Founded: 2018

What We Do

Rubiscape is a decision intelligence platform that unifies business intelligence, analytics, data science, and artificial intelligence in one place, helping organizations move from BI to AI. Its technology and product-development work spans AI-focused development, software engineering, product management, agile delivery, security operations, and DevOps, reflecting a software platform mission centered on enabling data-driven decisions across modern organizations.

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