Founding AI Engineer @ Embedded AI Efficiency Layer, Berlin

Meyandy LLC; Berlin; Vor Ort; EUR 120.000 - 160.000; Vollzeit

Zusammenfassung

Embedded AI Efficiency Layer is seeking a Founding AI Engineer in Berlin to partner with founders, shape architecture, and drive core product development from the ground up.

You will own major technical decisions, build production systems, and tackle complex research challenges while delivering reliable, scalable AI infrastructure and APIs for enterprise deployments.

Qualifikationen

• Strong software engineering background and production-grade code experience.
• Experience with backend systems and API development.
• Hands-on work with LLM APIs and production AI systems.
• Cloud infrastructure experience and containerization with Docker/Kubernetes.

Aufgaben

• Research and productionise AI cost-efficiency, context optimization and token reduction.
• Build across context selection, compression, caching and model routing.
• Develop APIs and an OpenAI-compatible gateway for enterprise use.
• Create reproducible cost-quality evaluations and quality gates.
• Own production reliability: monitoring, deployments, incidents, capacity and latency.

Kenntnisse

Python

TypeScript

APIs

Backend systems

Cloud infrastructure

LLM basics

Tools

Docker

PostgreSQL

Kubernetes

vLLM

LiteLLM

Jobbeschreibung

About the Venture

This is an Atlantic portfolio venture. About the Venture AI is being integrated into more products every month, and every interaction consumes tokens. As usage scales, costs add up quickly. The first race was adoption. The next is efficiency: inference costs increasingly determine what companies can afford to build and ship. We’re building the efficiency layer for production AI. Our systems make AI dramatically leaner, reducing token usage and lowering the cost of every interaction without compromising the quality standards that matter. Over time, we aim to improve both cost and quality, so companies can do more with AI rather than choose between better performance and a healthier bottom line. We closed our pre‑seed in just three weeks and are now preparing our first customer pilots. The pace is high and the timelines are ambitious. We are aiming for something big, and that requires a lot of input from every member of our early team.

About the Role

You’ll join as our first AI engineer and work directly with the founders to build the core product from the ground up. You’ll own major areas of product development, help define our architecture and technical direction, and turn complex research and engineering problems into reliable production systems. This role requires someone who can think deeply about AI systems and write the code to build them. You’ll work across AI infrastructure, backend systems, evaluation and enterprise deployments, with substantial ownership over the technical decisions behind the product.

What You’ll Do

• Research, invent and productionise systems for AI cost efficiency, context optimisation and token reduction.
• Build across context selection, compression, caching, model routing, tool-call reduction, retry control and output budgets.
• Develop APIs, an OpenAI-compatible gateway and integrations with model providers and enterprise AI applications.
• Create reproducible cost-quality evaluations, regression tests and quality gates.
• Own production reliability across monitoring, deployments, incidents, capacity, availability and latency.
• Build secure enterprise infrastructure with tenant isolation, access controls, secrets management and protected customer data.
• Optimise distributed-system performance across throughput, caching, rate limits, resource usage and failure handling.
• Translate early customer requirements into reliable product capabilities.
• Take on the broad day‑to‑day engineering work required to move an early product forward.

About You

You’re an experienced AI engineer who combines strong software engineering with original thinking about how production AI systems can become more efficient. You can reason from first principles about where cost and quality are lost, test new approaches rigorously and turn the strongest ideas into production‑grade code. You have substantial experience in software engineering, backend systems and API development. You are highly proficient in python or TypeScript or at least some coding languages and comfortable working across them. You understand the foundations of modern LLM systems, including tokenisation, context management, inference behaviour, model evaluation and the trade‑offs between cost, latency and quality. You have hands‑on experience building with LLM APIs and understand the behaviour, cost and reliability challenges of production AI systems. You have practical experience designing experiments and evaluations that measure both model quality and system performance. You have worked with cloud infrastructure, PostgreSQL and Docker. Kubernetes experience is a strong advantage. Experience with vLLM, SGLang, LiteLLM or similar AI infrastructure is highly relevant. You understand distributed‑system performance, including latency, throughput, caching, rate limits and failure handling. You can independently research difficult problems, test hypotheses and translate technical ideas into working systems. You write …

Founding AI Engineer @ Embedded AI Efficiency Layer, Berlin — atlantic.vc, Berlin.