Agentic Ops Intern

Agentic Ops Intern THE OPPORTUNITY As an Agentic Ops Intern, you'll build systems that take on real operational work — not prototypes, not demos. You'll turn messy, human processes into agents that execute consistently, reliably, and at speed. You'll architect and ship agents end-to-end: define the problem space, design multi-agent orchestration patterns with shared persistent state, build the tooling and memory layers that let agents compound intelligence over time, and iterate based on real production usage. You’ll work across the full stack of agent infrastructure — from intent classification and context assembly to feedback synthesis and tool integration — building systems that define problems clearly, drive decisions, and execute reliably in real-world business workflows. You'll work closely with operators and engineers to identify where agentic leverage exists, then drive solutions forward. You'll operate with autonomy, but not in isolation — our team provides context, feedback, and support as you build. When something is unclear, you bring clarity. When something breaks, you move to fix it. Strong interns don't just complete projects — they build systems that become part of how we operate. The best turn that into a full-time role. This opportunity is fully remote and operates within +/- 3 hours of EST. WHAT YOU’LL DO & LEARN - Design, build, and deploy agent-driven systems for key workflows (talent, onboarding, internal tooling) — ensuring adoption and real impact on how the business runs - Identify and prioritize high-impact opportunities where agent-driven systems can create leverage, and translate ambiguous business problems into scalable, executable solutions. - Design and refine agent behavior — prompting, memory, tools, and orchestration — to improve performance over time - Own a system end-to-end and its performance: accuracy, speed, reliability, and adoption improve because you’re in the loop - Work closely with internal users to ensure what you build is trusted, used, and embedded into daily workflows - Identify opportunities to streamline, accelerate, or automate fragmented work through adaptive, agent-based systems - Document what you build so it scales across the team — not just for you, but for others to reuse and extend ABOUT YOU - You’re actively exploring or building with AI agents — you’re curious, hands-on, and like testing what’s possible - You think in systems — inputs, outputs, feedback loops, and where things break - You can operate in ambiguity and make progress — you don’t need everything defined to get started - You care about outcomes — not just demos, but systems that hold up under real use - You take ownership of your work and move problems forward, pulling in others when it helps you get to a better result - You learn quickly across domains — technical, operational, or wherever the problem is - You build with iteration in mind — ship, observe, improve, repeat PREFERRED EXPERIENCE - Final-year student (undergraduate or grad program), recent grad — or early in your career and already building with intent - You’ve experimented with designing multi-tier agent memory architectures (persistent, episodic, and learned knowledge layers) and orchestrating multi-agent systems with shared state, feedback loops, and compounding intelligence over time. - You’ve found your way into building with technology — through school, projects, or a self-directed path — and can point to things you’ve shipped - You’ve experimented with LLMs, agents, or automation tools (OpenAI APIs, LangChain, Zapier, etc.) beyond just following tutorials - You can code well enough to prototype, test, and iterate (Python or similar) - You’ve had exposure to workflows, operations, or systems — and have some sense of how real work gets done - You’ve built side projects, tools, or experiments that improve real tasks — shipped, used, and iterated on (this matters more than credentials) If you’ve built things ... (truncated, view full listing at source)