Staff Backend Engineer, AI Systems

You will design and build the core AI systems and platforms that enable Mural’s next wave of agentic, AI-driven collaboration experiences.

Responsibilities

Build the core backend systems that power Mural’s agent platform, including orchestration, durable execution, tool execution, memory, observability, and evaluation infrastructure; Design scalable services and APIs that allow AI agents to retrieve context, coordinate multi-step workflows, interact with Mural data, and act reliably on behalf of users; Develop the agent memory layer, including systems for conversation context, product context, retrieval, summarization, compaction, and long-term context management; Create infrastructure to monitor, debug, and improve agent behavior through traces, metrics, feedback loops, and offline evaluation; Translate complex, open-ended product needs into clear backend architectures, service boundaries, data models, and implementation plans that align technical capabilities with user value; Help define the technical direction for agentic AI at Mural, contributing to long-term architecture and strategy; Champion engineering excellence, mentoring others and establishing best practices for building reliable AI systems; Contribute to team growth through hiring, process improvements, and fostering a culture of curiosity, collaboration, and inclusivity

Requirements

7+ years of software engineering experience, with strong expertise designing, building, and operating reliable production systems, scalable services and APIs, and well-defined system architectures; Experience designing and operating distributed systems for complex workflows, including orchestration, asynchronous processing, job execution, retries, event-driven architectures, long-running processes, and failure recovery; Familiarity with AI, LLM, or agentic systems, including concepts such as tool use, context retrieval, evaluation, or model orchestration; Strong focus on production quality, including observability, reliability, testing, security, maintainability, and incident response; Strong communication skills, with the ability to produce clear technical documentation and collaborate cross-functionally; Experience working full stack or collaborating closely on product-facing frontend experiences; Deeper AI/ML experience, especially with LLM evaluation, experimentation, embeddings, retrieval systems; Experience with knowledge graphs, graph-based data modeling, entity resolution, or relationship-aware retrieval systems