AI-Driven Conversational Platform Architect

4 days ago

Bhavnagar, Gujarat, India beBeeEngineer Full time ₹ 20,00,000 - ₹ 25,00,000
Job Opportunity

We're looking for a highly skilled senior full-stack engineer to join our team and help design and build an innovative AI-driven conversational platform. The ideal candidate will have experience in architecting scalable systems that integrate multiple large language models (LLMs), support real-time interactions, handle complex state management, and ensure performance, observability, and security across the stack.

The role involves implementing advanced chat session management, including context persistence, token optimization, and retrieval-augmented generation (RAG). Additionally, you'll be responsible for designing and optimizing high-throughput APIs with rate limiting and fault tolerance, integrating token metering, analytics, and usage-based billing systems, and developing a secure, multi-tenant user management system with granular authentication/authorization.

You'll also leverage event-driven architectures for real-time processing and monitoring, optimize database schemas and queries for low-latency chat history retrieval, implement vector search and RAG pipelines using Pinecone, Weaviate, or pgvector for knowledge grounding, and ensure cloud-native scalability with Docker/Kubernetes, CI/CD pipelines, and infrastructure as code (IaC).

As a senior full-stack engineer, you'll work closely with the development team to set up observability for debugging and performance monitoring, apply AI safety and guardrails, and stay ahead of AI ecosystem developments to propose new integrations.

Key Responsibilities:
  1. Implement advanced chat session management.
  2. Design and optimize high-throughput APIs.
  3. Integrate token metering, analytics, and usage-based billing systems.
  4. Develop a secure, multi-tenant user management system.
  5. Leverage event-driven architectures for real-time processing.
  6. Optimize database schemas and queries.
  7. Implement vector search and RAG pipelines.
  8. Ensure cloud-native scalability.

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