Agentic Analytics Products Developer
eBay
- Location
- Bengaluru, India
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 314 approvals (FY2023)
- Posted
- Aug 19, 2026
Skills
About this role
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts. Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet. Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all. Analytics is undergoing a fundamental shift, from traditional data science toward AI-driven analytics product development. As business intelligence evolves into intelligent, AI-powered tooling, we are looking for someone eager to help lead this transformation. This role sits at the intersection of analytics, product, and AI. You will play a key part in reimagining our Business Intelligence ecosystem as a suite of AI-native applications, stepping into the role of an AI Analytics Product Manager. We are building toward a future where business and product teams can diagnose performance, uncover insights, and take action through AI-enabled experiences. If you’re motivated to move beyond analysis into productizing intelligence and want to shape how eBay interacts with data in the AI era, this is an opportunity to be at the forefront of that journey.
About the role
Build the platform and infrastructure that powers AI agents for analytics products at scale. Own the core systems behind data retrieval, prompt orchestration, chatbot experiences, and grounded answer generation. Work closely with middleware, platform, and product engineering teams to ensure reliable integration, observability, safety, and performance across the stack. Partner with Legal, Privacy, Security, and Responsible AI to ship compliant, trustworthy AI capabilities without slowing execution. 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. Work closely with middleware teams to ensure clean integration patterns, service contracts, streaming support, and operational reliability. Deploy and operate services in containerized environments with strong attention to scalability and reliability. Analyze production failures and optimize for quality, latency, reliability, and predictable cost. Key skills 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. Ability to partner effectively with middleware