- Company Name
- Freshworks
- Job Title
- Backend AI Platform Engineer
- Job Description
-
Job title: Backend AI Platform Engineer
Role Summary
Design and build core backend services that power an agentic AI platform, enabling reasoning-driven agents, multi‑agent orchestration, dialog management, and outcome‑based workflows. Collaborate with AI architects to deliver high‑performance APIs, runtimes, and integrations with LangChain, LangGraph, and LangSmith.
Expectations
- 7+ years of backend engineering, 2+ years in AI/ML platform development.
- Proficiency in Java and Python.
- Deep experience with distributed, event‑driven microservices; cloud‑native architecture.
- Hands‑on work on Agentic AI stack and enterprise‑grade backend services.
Key Responsibilities
- Build agent runtime orchestration services (reasoning, planning, tool invocation) integrating LangChain/LangGraph.
- Develop APIs/SDKs for agent workflow creation, deployment, and management.
- Create stateful dialog management and memory services for multi‑turn agents.
- Implement multi‑agent communication protocols and shared context.
- Design cloud‑native, event‑driven architecture, microservices or service mesh.
- Orchestrate task scheduling and long‑running workflows via Temporal, Airflow, or similar.
- Develop real‑time message buses (Kafka, Pub/Sub) for agent communication.
- Optimize LLM orchestration for performance and cost using caching, batching, token monitoring.
- Integrate enterprise systems, APIs, and knowledge sources (REST, GraphQL, gRPC).
- Work with vector databases (Elasticsearch, Pinecone, Weaviate, FAISS) and RAG pipelines.
- Build secure multi‑tenant services, RBAC, API auth, tenant isolation.
- Implement compliance guardrails (rate limiting, safe tool usage, content filtering).
- Write comprehensive test suites (unit, integration, load).
- Implement logging, tracing, metrics (OpenTelemetry, Prometheus, Grafana).
- Participate in on‑call rotations, enhance platform resilience.
Required Skills
- Java, Python programming.
- LangChain, LangGraph, LangSmith ecosystems.
- Distributed systems, event‑driven architecture, microservices.
- Cloud (AWS), Kubernetes, IaC (Terraform, Helm).
- Databases: PostgreSQL, Redis, MongoDB; vector DBs: Elasticsearch, Pinecone, FAISS, Weaviate.
- Workflow orchestration: Temporal, Airflow.
- Messaging: Kafka, RabbitMQ.
- AI/LLM knowledge: OpenAI, Anthropic, Azure OpenAI, prompt/tool orchestration.
Preferred Skills
- Conversation orchestration, dialog state tracking, AI planning.
- Enterprise security (RBAC, SSO/OAuth2, encryption).
- SaaS platform development in startup/high‑growth context.
Required Education & Certifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- No mandatory certifications required, but experience with relevant cloud or security certifications (e.g., AWS Certified Solutions Architect) is a plus.