Senior Backend Engineer for AI Orchestration

2 days ago

Taguig, National Capital Region, Philippines beBeeBackendDeveloper Full time ₱5,500,000 - ₱8,500,000
Job Overview

We're building a platform that utilizes autonomous AI agents for data collection, labeling, and intelligent analysis.

This system requires an experienced developer to power its core services. The ideal candidate will be responsible for architecting and implementing services that interface with LangGraph-based workflows, manage data access from structured and unstructured sources, and support seamless orchestration between our AI layers and data infrastructure.

Key Responsibilities
  • Design and develop performant backend APIs and services using AWS Lambda, EC2, and RDS.
  • Integrate data access layers with LangGraph and LangSmith agents to enable efficient data retrieval.
  • Architect retrieval pipelines using vector databases to facilitate semantic search for AI agents.
  • Collaborate with data engineers to support Retrieval-Augmented Generation (RAG) workflows across a shared data lake.
  • Develop and maintain task routing, memory management, and agent orchestration logic.
  • Contribute to platform-level observability, metrics, logging, and diagnostics for agentic tasks.
  • Deploy and manage Model Context Protocol (MCP) servers to wrap scraping, proxy, and JS-rendering tooling as standardized services.
Requirements
  • 4+ years of experience in backend development with strong programming skills in Python or Node.js.
  • Deep understanding of serverless architectures, microservices, and AWS technologies like Lambda, EC2, and RDS.
  • Familiarity with LangGraph, LangChain, or equivalent AI orchestration frameworks.
  • Working knowledge of vector databases like Chroma and Pinecone, and semantic search concepts.
  • Solid expertise in database and API design, particularly with PostgreSQL.
  • Experience building scalable, low-latency backend systems for AI or data platforms.
Preferred Qualifications
  • Experience with agentic AI systems or orchestration of multi-agent workflows.
  • Understanding of RAG patterns in production environments.
  • Comfortable with Databricks and Unity Catalog data integration strategies.
  • Exposure to AWS Bedrock and large model orchestration in cloud-native environments.

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