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 i
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 i
Requirements:
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.
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.
This position is open to all candidates.
