Build multimodal RAG systems, including development and optimization of key modules such as recall, ranking, long-text processing, and multi-document synthesis.
Develop the Agent's tool layer, integrating external APIs and MCP such as search, code interpreters, browsers, sandboxes, and third-party services.
Design and tune prompts and context management, with tailored optimization for different product requirements....
Develop the foundational platform for AI Agents - including agent registry, evaluation framework, prompt management, vector stores, memory layers, and tool integrations
Build robust data pipelines and feature pipelines that feed AI Agents with high-quality structured and unstructured data from our data lake ecosystem
Implement guardrails, safety checks, hallucination detection, and human-in-the-loop systems to ensure trustworthy and responsible AI...
Demonstrated experience across the Agent Development Lifecycle: specification, harness build, tool and MCP integration, evaluation, deployment, observability, and refinement.
Proven track record deploying software systems in production with measurable results — reliability, performance, or business value outcomes.
Experience with knowledge layer engineering: RAG pipelines, MCP-connected sources, Text-to-SQL, Elasticsearch, and knowledge graph design....
This role is highly cross‑functional and customer‑facing. You understand software development workflows, care deeply about developer tools, and love helping engineering organizations succeed at scale.
Build and grow deep relationships with engineering leaders and power users at key accounts
Partner with Field Engineering and Sales to deliver a seamless post‑sale experience...