Sr. Applied AI Engineers (multiple openings)

Summary Multiple early-stage portfolio companies (Seed/Series A) are hiring engineers to build the next generation of AI-native systems across enterprise software, security, healthcare, developer tools, and vertical SaaS. These companies are building systems that go beyond copilots — software that reasons, takes action, and executes real-world workflows end-to-end. While each company operates in a different domain, they share a common set of technical challenges: goal-driven execution, multi-step reasoning, system reliability, and increasingly, coordination across multiple agents and tools. This is not a single role at one company. Applicants will be considered for multiple openings across Greylock-backed companies, and we will work directly with you to match you with the most relevant teams based on your experience and interests. What You’ll Do Design and build agent systems that execute multi-step workflows across real-world environments Develop goal-driven systems that plan, act, and adapt in the face of ambiguity Contribute to or lead the design of multi-agent architectures, where systems coordinate to complete complex tasks Build orchestration layers that manage tool use, decision-making, and long-running workflows Define and implement reliability mechanisms including evaluation, guardrails, recovery, and human-in-the-loop systems Drive system performance across latency, cost, and quality in production Partner with founders, product, and engineering teams to translate open-ended problems into working systems Help set technical direction and establish best practices as teams scale Where You’ll Work in the Stack Orchestration: workflow management, tool routing, multi-component systems Execution: integrations with APIs, services, and real-world systems State & Memory: persistent context, user/system state, temporal reasoning Evaluation & Control: feedback loops, safety systems, observability Infrastructure: deployment, scaling, monitoring, and performance optimization What We’re Looking For Experience building and shipping production LLM or agent-based systems that take actions, not just generate outputs Strong understanding of goal-driven execution and multi-step workflows Experience with orchestration, tool use, or multi-component systems (e.g., ReAct, LangGraph, or similar approaches) Track record of owning systems end-to-end, including reliability and iteration in production Comfort working across the stack, from model behavior to system integration Strong engineering fundamentals (Python or similar; experience building production systems required) Ability to operate in ambiguous environments and make high-leverage technical decisions Signals We’re Especially Excited About You’ve built systems that complete workflows end-to-end, not just assist users You’ve worked on agents that operate over time (stateful, proactive, or long-horizon systems) You’ve designed or contributed to multi-agent or multi-component systems You’ve owned failure modes, reliability, and recovery in production systems You’ve integrated AI systems with external tools, APIs, or enterprise environments You’ve built from first principles in early-stage settings #J-18808-Ljbffr Greylock Partners