Senior Software Engineer, Agents

Responsibilities Build the AI Runtime Design and implement the orchestration layer that turns natural-language intent into reliable execution. Build systems for entity resolution, context assembly, connector orchestration, and evidence retrieval. Develop reusable Skills that encapsulate business workflows and domain expertise. Build routing systems that intelligently coordinate connectors, tools, deterministic logic, and multiple language models. Build Products Users Trust Own features end-to-end, from runtime capability to user-facing experience. Develop evidence-backed reasoning with citations and traceability that users can actually see and verify. Build evaluation frameworks that continuously improve quality. Implement permission models, freshness validation, and action policies that work transparently for end users. Ship and Iterate Build prototypes, validate ideas, and rapidly iterate with customers. Write high-leverage code that enables entire product areas. Collaborate closely with Product, Design, Sales Engineering, and Customer Success to turn ambitious ideas into production systems. Experiment with new agent architectures while maintaining production-grade reliability. Requirements 7+ years of software engineering experience building production systems. Deep understanding of distributed systems and backend architecture. Experience building AI applications using LLMs, agents, RAG, MCP, or modern AI frameworks. Strong software engineering fundamentals including APIs, concurrency, testing, and system design. Experience building developer platforms, orchestration systems, or workflow engines. Ability to rapidly prototype while maintaining production quality. Strong product instincts and comfort operating in ambiguous environments. Exceptional written communication skills. A bias toward ownership and shipping. Nice To Have: Experience building AI agents or agent frameworks, including evaluation systems. Familiarity with orchestration frameworks (LangGraph, Temporal, MCP, or similar). Experience with retrieval systems, vector search, or knowledge graphs. Experience building developer tools or platform infrastructure. Experience with data infrastructure including Kafka, Iceberg, Postgres, Spark, or modern data warehouses. #J-18808-Ljbffr