Senior Machine Learning Engineer (Agent Systems)

About e:cue e:cue is a fast-paced, high-growth startup building custom AI analysts for leaders in marketing, finance, and revenue. Our platform combines production-grade application services, cloud infrastructure, and agent systems that power high-stakes business decisions. We're looking for a senior engineer who can take work from ticket to outcome: scope it, build it, ship it, and own it in production. Role Overview This role owns core parts of the agent stack, deciding how agents plan and execute, how they interact with data, and how we evaluate and improve them over time. You'll work across: Agent systems: planning, tool use, multi agent orchestration, long-context workflows Backend and infrastructure: agent services, data pipelines, and observability Evaluation and post-training: Designing evaluation harnesses, feedback loops, datasets, and improving agent behavior What You'll Do Design and build production agent systems: Tool execution frameworks (MCP servers, sandbox environments, tool architectures) Planning and reasoning pipelines Context and dependency aware agent execution Own services that power production agents: Reliability, latency, and scaling improvements Observability integrity (logging, tracing, evaluation hooks for offline and online evaluation) Develop evaluation and feedback systems: Define metrics for agent performance (offline and online) Own evaluation harnesses and test suites Instrument systems to generate high-quality evaluation and training data C