Lead AI Engineer

Lead AI Engineer (Hands-On) – Production GenAI SaaS

Germany (Hybrid) Highly Competitive Base Salary, Bonus & Benefits

We are partnering with a globally recognised consultancy building a dedicated AI Lab focused on developing scalable, client-facing AI SaaS products.

This is a hands-on engineering leadership role for someone who has built and operated external SaaS products used by real customers — and who understands how to take AI systems from concept to secure, scalable production.

This is not a research or experimentation role. The focus is on production-grade architecture, performance optimisation, and long-term maintainability.

The Role

You will play a key role in architecting and building advanced AI-powered SaaS products leveraging LLMs and modern GenAI frameworks.

Key responsibilities include:

Designing and building multi-tenant SaaS architectures Implementing advanced RAG-based LLM systems in production Developing scalable data pipelines integrating structured and unstructured data Deploying and operating AI systems securely on AWS Optimising latency, inference cost, and system performance Establishing engineering standards and ensuring production quality Collaborating closely with product and leadership teams Providing occasional technical input into client proposals

This role remains deeply hands-on, you will actively write and review production code.

What We’re Looking For

Proven experience building and scaling external, customer-facing SaaS products Strong understanding of multi-tenant architecture and distributed systems Production experience with LLM-based systems (RAG, evaluation frameworks, guardrails) Strong Python and experience with modern AI frameworks (Hugging Face, LangChain, PyTorch) Deep experience with AWS Solid understanding of performance optimisation, cost control, and system reliability High engineering standards and strong collaboration skills

Why This Role? Work on serious, production-grade AI products — not internal tools or PoCs High level of ownership and architectural influence Strong technical environment with ambitious AI roadmap Opportunity to build scalable GenAI systems at enterprise level