About the role
Organizations everywhere struggle under the crushing costs and complexities of “solutions” that promise to simplify their lives. To create a better experience for their customers and employees. To help them grow. Software is a choice that can make or break a business. Create better or worse experiences. Propel or throttle growth. Business software has become a blocker instead of ways to get work done. There’s another option. Freshworks. With a fresh vision for how the world works. Freshworks Inc. builds uncomplicated service software that delivers exceptional employee and customer experiences. Our people-first approach to AI eliminates friction, helping businesses reduce complexity, lower cost-to-serve, and deliver faster, more human support through enterprise-grade yet easy-to-use CX and IT solutions. Nearly 75,000 companies, including Bridgestone, New Balance, Nucor, S&P Global, and Sony Music, trust Freshworks to power their Employee Experience (EX) and Customer Experience (CX) operations. Fresh vision. Real impact. Come build it with us. We are seeking a Backend AI Platform Engineer to lead the development of core backend services powering our Agentic AI Platform. In this role, you will be the primary technical driver for building reasoning-driven agents, multi-agent orchestration, and outcome-based workflows. You will collaborate with the Principal AI Architect to bridge the gap between high-level design and scalable implementation. You will own the development of high-performance APIs and orchestration runtimes, integrating frameworks like LangChain, LangGraph, and LangSmith. This role is highly hands-on and requires a technical leader who can navigate a fast-paced environment while maintaining high engineering standards. Key
Responsibilities Platform Backend Development 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