AI Tech Lead | Agent Platform & Enablement

Job description

Scope: Hands-on technical lead, no direct reports — influence across Copilot & AI, Pipeline, and Experience About Miggo We're Miggo — a cybersecurity startup on a mission to stop app-layer breaches before they happen. Founded in 2023 and backed by top-tier cyber VCs, we're building the world's first Application Detection & Response (ADR) platform. Why? Because 80% of cyber attacks target the app layer, and current tools just don't cut it. Miggo brings visibility into how apps actually behave at runtime, spotting risky flows and shutting down threats in real time. We're closing the patch gap: showing security teams what's reachable, what's exploitable, and what's being attacked right now — and delivering targeted mitigations when a patch isn't ready. At Miggo, we live by four core values: We make it customer-focused — user needs are our north star. We make it happen — driven by execution and a can-do mindset. We make it better — always pushing boundaries and learning fast. We make it together — one team, thriving on collaboration and diverse perspectives. About the Role Miggo already runs agents in production. Our WAF Copilot takes a freshly disclosed CVE and turns it into a validated, provider-specific WAF rule — a state-driven agent graph that researches the vulnerability, maps the attack surface, composes the rule, then attacks its own output with an independent bypass judge and a false-positive prober before a human is ever offered a deploy. When a weakness survives, the system downgrades its own recommendation and records what it could not prove. That last part is the thesis of this role. An agent that touches production security must prove it works and declare what it couldn't prove. The security industry is about to be flooded with agentic claims nobody can verify. We intend to be the company that made verification legible — and that starts with holding our own agents to a standard we're willing to publish. We're looking for an AI Tech Lead to own that standard across three surfaces: The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter — with evaluation, observability, and cost control built in rather than bolted on. Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere — engineering, research, product, GTM — through tooling, patterns, and teaching. The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public. This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain it. What You'll Do Define and build Miggo's agent framework — shared components, orchestration patterns, tool interfaces, and conventions that make "how do I build an agent here" a five-minute answer. Make evaluation a gate, not an afterthought : trajectory testing, golden datasets, offline replay, and per-dimension scoring that runs in CI. Land the release benchmark so promote / hold / rollback is a number, not a vibe. Own agent observability end to end — the execution graph, tool invocations, intermediate reasoning, latency per step, and quality drift — including the external Temporal-orchestrated flows that are hardest to introspect today. Own the economics : provider abstraction, model routing by task complexity, small-model substitution where it holds, cost attribution per flow. Thousands of CVEs through a labeling agent is a budget line, not a detail. Drive latency and determinism in our production agent flows — tighter loops, early stopping, deterministic state machines over prose-in-prompt orchestration. Raise the company's AI fluency. Build the internal tooling, skills, and playbooks that let every team — not just R&D — work AI-natively, and teach the judgment for when not to. Partner with security research, product, and engineering leadership so agent capability and product roadmap actually converge. What You'll Have You've shipped agentic systems to production — real orchestration, tool use, structured outputs, and the failure modes that only appear at scale. Not "I've called an LLM API." You've built the evaluation discipline , not just consumed it: trajectory tests, golden datasets, regression gates, offline replay. "It seems better" is not a metric, and you have opinions about what is. Deep backend and distributed-systems engineering. Strong Python, and comfort with workflow orchestration (Temporal or equivalent), streaming, and cloud-native infrastructure. Agent platforms are systems problems wearing an AI hat. Fluency across the modern agent stack — LangChain/LangGraph-style frameworks, multi-provider routing, structured output contracts, prompt and context engineering — with the judgment to know which parts are load-bearing and which are fashion. Security literacy. Enough to reason about whether an agent's security output can be trusted, and to argue with researchers on the merits. You don't need to be a vulnerability researcher. Influence without authority. You'll change how three teams work with no one reporting to you. Show us where you've done that. Advantage : experience with AI/LLM security — red-teaming agents, prompt injection, or agentic attack patterns. Advantage : background in cybersecurity, detection engineering, or WAF/mitigation systems. Advantage : you've driven AI adoption across a whole company, not only an engineering org. We deliberately don't list a years-of-experience bar. Agent engineering is a few years old as a discipline — we care what you've shipped and what you learned when it broke. Why Miggo? Most "AI lead" roles are a greenfield promise. This one isn't: there are real agents in production, real customers behind them, and a genuinely hard standard already half-built. You'll get the leverage of setting how an entire company builds with AI, the autonomy of a hands-on lead with no layers to negotiate, and a platform to argue the methodology in public while the category is still being defined. We're small enough for your conventions to become how Miggo works — and bold enough to publish them. <!-- notionvc: ed497ce1-f06b-42c5-be56-ef1286b4799f -->