Director of Engineering

NXT; Berlin; Hybrid; EUR 140,000 - 190,000; Full time

Job summary

NXT in Germany is seeking a Director of Engineering to define the architecture of an AI-native operations platform. You will translate real client pain points from regulated industries into scalable product components and lead a small elite team embedded in production engagements.

This is a hands-on leadership role in a production-focused environment, where coding agents are part of the default, and governance, observability, and reliability are built from day one.

Qualifications

• Strong backend engineering background with end-to-end B2B system delivery.
• Experience with LLMs in production beyond demos.
• Experience in regulated sectors (banking/healthcare) and production-grade systems.

Responsibilities

• Define architecture for an AI-native operations platform.
• Build and lead a small elite product and engineering team.
• Hands-on contribution to core platform components in client engagements.

Skills

Backend engineering

LLM systems in production

Regulated environment experience

Staff+ leadership

German language

Job description

I left McKinsey in March to build again.

After years of business building and GenAI work in regulated mid-market environments, one thing became clear: the bottleneck in AI is not capability. It is turning capability into reliable systems that operate inside real businesses. Most companies experiment with AI. Very few build systems that are governed, production-grade, and embedded in operational workflows.

.NXT closes that gap. We are an AI Operations company — we build and run AI systems for regulated mid-market companies and PE portfolios in DACH. Not consulting: production systems with operational accountability, deployed into finance, back office, and operational workflows, creating measurable value in weeks.

Five months in, this is no longer a thesis. We have anchor clients in banking and healthcare, seven-figure revenue in year one, a team of seven, and ISO 27001 certification underway — fully bootstrapped, funded by client revenue from day one.

To build the platform and product behind this, I am looking for a Director of Engineering.

How We Build

We do not build the platform in isolation. We build it inside real, paying client engagements in regulated industries — currently banking and healthcare — and we own the reusable IP that emerges. The first engagements are the birthplaces of the first platform components. This is a deliberate choice. The platform runs in production from day one, in regulated environments, with real operational data and real consequences. The role requires someone who sees this clearly: in this phase, the engagement is the engineering environment. Building inside real operations is not a constraint on platform thinking — it is the only path to a platform that survives contact with reality.

The Role

This is a foundational product and engineering leadership role — a co-development partner for the founder. You will help define what we build, how we build it, and how product and engineering evolve as the company scales. You will not inherit a traditional engineering organization. You will help build a small, elite product and engineering team operating in an AI-native way, with coding agents deeply embedded into how work gets done. This is a builder role first: in the early phase you work hands‑on on core platform components and operate as senior technical lead inside client engagements.

What You Will Do

Product & platform architecture: Design the architecture of an AI-native operations platform. Translate real operational pain points — observed inside live engagements — into scalable product components. Define clear boundaries between deterministic workflows and agentic systems. Ensure reliability, observability, and governance in production.

AI-native engineering organization: Build a small, elite product and engineering team. Integrate coding agents and automation deeply into the development workflow. Establish a way of building where human judgment and machine leverage are combined by design — fast development loops without compromising core system guarantees.

Execution inside real engagements. Work hands‑on on core platform components. Turn messy operational workflows into stable systems. Close the gap between product design, architecture, and production reality.

Technical Challenges

• Safe execution boundaries between deterministic and agentic logic
• Workflow infrastructure for long-running, stateful operational processes
• Integrations across ERP, finance, inbox, and document systems
• Making AI systems observable, governable, and debuggable in production
• Retries, partial execution, failure modes, and approval logic across complex workflows
• An engineering environment where coding agents are part of the default development model

What You Need

• Strong backend engineering background — you have designed, built, and shipped B2B systems end-to‑end, and you can still carry core components yourself
• LLM systems in production: designed, deployed, and operated — beyond experimentation and demos
• Experience in or genuine respect for regulated environments (banking, insurance, healthcare) & what production-grade means there
• Experience building or leading small engineering teams — or a Staff+ engineer ready to make that step deliberately
• Comfort operating client‑facing in senior settings; you can hold an architecture discussion with a CIO and a compliance officer in the same meeting
• Business-fluent German is a strong plus — our client environments are German-speaking

Who This Is For

It is not a fit for pure strategy or product profiles without an engineering foundation, research-focused ML backgrounds without shipping track record, or leaders who need an existing organization around them. We are early. This is Aufbauarbeit — deliberate, funded, and already in production, but Aufbauarbeit.

Practicalities

Düsseldorf is our center of gravity; Berlin works with regular presence at clients in NRW. Hybrid by default. Start as soon as your notice period allows.