About the role

At eBay's Bengaluru, India office (Hybrid), this Agentic Analytics Products Developer role reimagines the Business Intelligence ecosystem as AI-native applications. You will build and scale platform infrastructure for AI agents powering analytics products, owning core systems for data retrieval, prompt orchestration, chatbot experiences, and grounded answer generation. Day-to-day work includes designing prompts and orchestration flows, developing RAG pipelines, building evaluation frameworks, and deploying containerized services while partnering with middleware, product, Legal, Privacy, Security, and Responsible AI teams.

What you’ll do

Build and scale AI platform infrastructure for agentic analytics and chatbot products
Design and maintain AI user prompts, system prompts, tool prompts, and orchestration flows for reliable task execution
Develop chatbot capabilities and agent workflows for analytics use cases
Build RAG pipelines across structured and unstructured sources, including SQL and documents
Improve retrieval quality through chunking, deduplication, hybrid search and embeddings
Build prompt and model evaluation frameworks for groundedness, accuracy, robustness, latency, and cost
Implement function calling, structured outputs, retries, fallbacks, and guardrails for production-grade agents
Analyze production failures and optimize for quality, latency, reliability, and predictable cost

What you’ll bring

Strong experience building production AI systems, LLM applications, or chatbot platforms
Deep understanding of prompt design, including user prompts, system prompts, tool prompts, and prompt iteration workflows
Hands-on experience with RAG systems, embeddings, vector stores, hybrid retrieval, and re-ranking
Experience building prompt evals, golden datasets, automated test harnesses, and regression checks
Strong Python engineering skills with experience building production APIs using FastAPI
Experience with LangChain and LangGraph for orchestration, tool use, and agent workflows
Experience deploying services with Docker and Kubernetes in production environments
Strong understanding of platform and infrastructure concerns such as scale, reliability, observability, and service integration

Nice to have

Experience with model routing, multi-step orchestration, and structured output systems
Background in AI safety, red-teaming, or jailbreak defense
Familiarity with analytics systems, query engines, or data platforms
Experience partnering with Legal, Privacy, Security, or Responsible AI teams

Skills

LLM application developmentPrompt design and orchestrationRAG and vector retrievalPrompt evaluation frameworksPython and FastAPILangChain and LangGraphDocker and KubernetesAI safety and guardrails