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# Staff Backend AI Platform Engineer

- **Company:** Melior AI, Inc.
- **Location:** San Mateo, CA, United States
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Automation of Tests, Software as a Service, Cloud Computing, Cloud Engineering, Code Review, Computer Programming, Data as a Services, Distributed Systems, Memory Management, PostgreSQL, Enterprise Messaging Systems, OAuth, Open Source Technology, Performance Tuning, Role-Based Access Control, Azure Machine Learning, Single Sign-On, Systems Architecture, Systems Integration, Workflow Management Systems, Pinecone, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Backend, Event Driven Architecture, Build Management, AI Platforms, LangSmith, Kubernetes, Weaviate, Apache Kafka, FAISS, Restful APIs, Terraform, Data Pipelines, Microservices, Agent2Agent Protocol
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/23_9EAD6368BA8BD3698ADD4D6AF2DB0DFC

## About the Role

6+ years of backend engineering experience. 1-2+ years of hands-on experience in AI/ML platform development. Expert Proficiency: Strong programming skills in Java and Python. Framework Expertise: Hands-on experience with LangChain, LangGraph, or LangSmith. Distributed Systems: Deep understanding of event-driven architectures, microservices, and Kubernetes. Cloud & Data: Solid experience with AWS, Terraform, and a mix of relational (PostgreSQL) and Vector databases. Orchestration: Practical experience with workflow engines like Temporal or Airflow and messaging systems like Kafka., Experience with AI-driven planning systems or dialog state tracking. Background in enterprise security (RBAC, SSO, OAuth2). Experience working in a high-growth SaaS or startup environment. Active contributions to open-source backend or AI frameworks.

## Description

Lead Implementation: Act as the lead engineer for agent runtime orchestration services, focusing on reasoning, planning, and tool invocation. API & SDK Design: Own the development of robust APIs and SDKs that enable internal and external teams to build and deploy agent workflows. State & Memory Management: Build and optimize stateful dialog management and memory services for multi-turn, context-aware agents. Agent Communication: Implement multi-agent communication (A2A) protocols and shared context systems.

System Architecture & Execution

Microservices Leadership: Execute the transition to cloud-native, event-driven backend services using microservices or service mesh architectures. Workflow Design: Build and manage task scheduling and long-running operations using tools like Temporal or Airflow. Performance Optimization: Optimize LLM orchestration for performance and cost through caching, batching, and token monitoring.

Integrations & Data Services

Data Pipeline Ownership: Implement and maintain RAG pipelines and integrations with vector databases (e.g., Pinecone, Weaviate, FAISS). Telemetry Integration: Ensure all backend services support LangSmith-based evaluation and comprehensive observability.

Security & Reliability

Tenant Isolation: Implement RBAC, API authentication, and multi-tenant isolation logic. Engineering Excellence: Set the standard for automated testing (unit, integration, load) and implement OpenTelemetry for full system visibility. Mentorship: Provide technical guidance and code reviews for more junior backend engineers on the team.