Engineering Manager - AI Engineering & AI Platform (m/f/x) at Scalable GmbH

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

18 Oct, 26

Salary

0.0

Posted On

20 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Engineering Management, AI Engineering, Platform Engineering, Python, AWS, Terraform, LLM Integration, CI/CD, Docker, API Design, Cloud-Native Architecture, Agentic Workflows, Backend Engineering, People Development, Analytical Thinking, Communication Skills

Industry

Banking

Description

Company Description Scalable Capital is a leading digital investment and banking platform with a full banking licence, empowering people across Europe to shape their own finances. Scalable Broker makes it easy and affordable for clients to invest professionally in stocks, ETFs, cryptocurrencies, and derivatives, as well as set up savings plans. Scalable Wealth, the digital wealth management service, offers clients professional investment in ETF portfolios, and is also adopted as a white-label solution by banks and other B2B partners. The company’s offerings are rounded off by attractive interest rates, loans, and private equity. With the European Investor Exchange, Scalable Capital offers an exchange specifically for retail investors. Over one million clients have already entrusted more than €30 billion to the platform. Founded in 2014, Scalable Capital now employs over 700 people across Munich, Berlin, Vienna, Milan, and London. Together with the founding and management team, including Erik Podzuweit and Florian Prucker, they are working on a new generation of financial services. Visit our finance blog or check out our Social Media channels to find out what our Expert Teams have to say. Our Company Values guide us every day in how we work and collaborate. To learn more about them, you can find our values here (English). Job Description Shape the future of our AI Engineering and AI Platform capabilities within the Data Science and AI tribe. We are building a new team of AI Software Engineers and AI Platform Engineers to bring AI use cases into production at scale. We are looking for a passionate and motivated Engineering Manager to lead this newly formed team. As the EM, you will play a key role in turning AI concepts, data science ideas, and business opportunities into scalable backend systems, cloud-native architectures, agentic workflows, and internal AI platform services. We are not training models from scratch. Instead, your team will integrate modern AI capabilities via APIs from providers such as OpenAI, Anthropic, Google, and others, and build the platform foundation required to use them securely, reliably, and cost-effectively. Build and lead a new AI Engineering and AI Platform team, helping engineers grow and the team become self-organized, agile, and autonomous Provide technical direction for AI/LLM services, backend systems, AWS architectures, Terraform infrastructure, CI/CD pipelines, and agentic workflows Drive the end-to-end implementation of AI use cases, from ideation and technical scoping to delivery, rollout, monitoring, and maintenance Shape our internal AI platform for model access, MCP server integrations, observability, governance, rate limiting, and cost management Work closely with Data Science, Product, Engineering, Security, Platform, and business stakeholders to identify and deliver high-value AI use cases Establish engineering best practices for reliable, secure, maintainable, and production-grade AI systems Be part of the recruitment process to attract and onboard new colleagues for the team Qualifications A university degree in a relevant field, such as Computer Science, Software Engineering, Mathematics, Natural Sciences, or a comparable qualification Previous experience in software engineering, backend engineering, platform engineering, cloud engineering, or AI engineering Experience leading engineers as an Engineering Manager, Team Lead, Tech Lead, or in a comparable role Strong understanding of scalable backend systems, cloud-native architectures, API design, and modern software development practices Good knowledge of modern AI system integration, including LLM APIs, agentic workflows, and production-grade AI services Hands-on experience with Python, Docker, CI/CD pipelines, cloud infrastructure, and Infrastructure as Code, preferably AWS and Terraform Understanding of AI platform topics such as observability, governance, data privacy, rate limiting, cost management, and secure LLM usage Passion for people development, technical excellence, and building high-performing engineering teams Strong analytical thinking, both in the technical and business domain Excellent communication skills that are clear, concise, and tailored to engineering, product, and business stakeholders Extreme sense of ownership and a pragmatic, hands-on mentality Experience with LangGraph, LiteLLM, Langfuse, Datadog, MCP servers, or similar technologies is a plus Additional Information Be part of one of the fastest-growing and most visible Fintech startups in Europe, creating innovative services that have a substantial impact on the lives of our customers Work with an international, diverse, inclusive, and ever-growing team that loves creating the best products for our clients Be productive with the latest hardware and tools Learn and grow by joining our in-house knowledge sharing or career development sessions and spending your individual Education Budget Learn and experience German culture first hand by joining our free German language classes International relocation support is provided if required Opportunity to work from abroad Benefit from an attractive compensation package and from the company pension scheme Monthly contribution of 50% for the ‘Deutschland Jobticket’ Say goodbye to order commissions and say hello to your complimentary subscription of Scalable Capital's PRIME+ Broker Enjoy flexible and discounted sports activities with Urban Sports Club

Responsibilities

Lead a new team of AI Software and Platform Engineers to transition AI concepts into scalable, production-grade backend systems. Drive the end-to-end implementation of AI use cases and shape the internal AI platform for model access, governance, and cost management.