Data Architectural Specialist

4 days ago

Manila, National Capital Region, Philippines beBeeBackend Full time $120,000 - $180,000
About Us

We're building a revolutionary platform of autonomous AI agents to collect, label, and analyze data. As a Senior Backend Engineer, you'll architect core services that interface with LangGraph-based workflows, manage data access from structured and unstructured sources, and enable seamless orchestration between our AI layers and data infrastructure.

This is a unique opportunity to design, develop, and deploy performant, production-grade backend APIs and services using AWS Lambda, EC2, and RDS. You'll integrate structured and unstructured data access layers with LangGraph and LangSmith agents, implement retrieval pipelines using vector databases to enable semantic search for AI agents, and collaborate with data engineers to support RAG workflows across a shared data lake.

Key Responsibilities
  • Backend Development: Design and develop high-quality, scalable backend APIs and services using Python and Node.js.
  • Data Access Integration: Integrate structured and unstructured data access layers with LangGraph and LangSmith agents.
  • Semantic Search: Implement retrieval pipelines using vector databases to enable semantic search for AI agents.
  • RAG Workflows: Collaborate with data engineers to support RAG workflows across a shared data lake.
  • Agent Orchestration: Develop and maintain task routing, memory management, and agent orchestration logic.
  • Observability: Contribute to platform-level observability, metrics, logging, and diagnostics for agentic tasks.
  • MCP Deployment: Deploy and manage MCP servers to wrap scraping, proxy, and JS-rendering tooling as standardized Model Context Protocol (MCP) services.
Requirements
  • A minimum of 4 years of experience in backend development with strong programming skills in Python and Node.js.
  • Deep experience with serverless architectures, microservices, and AWS (Lambda, EC2, RDS).
  • Familiarity with LangGraph, LangChain, or equivalent AI orchestration frameworks.
  • Working knowledge of vector databases (Chroma, Pinecone) and semantic search.
  • Solid database and API design expertise, particularly with PostgreSQL.
  • Experience building scalable, low-latency backend systems for AI or data platforms.

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