Senior Agentic AI Engineer
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Position Overview & Specifications
CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.Β
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Why us?
π CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the worldβs top financial institutions globally.
π In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. Weβre a fast-paced, high-performing team that thrives on pushing boundariesβcontinuously evolving our products, services, and operations. At CUBE, we donβt just keep up we stay ahead.
π± We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our βmake it happenβ culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.
π With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.
π‘ We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.
Role:
We are looking for an experienced LLM Engineer for our new Berlin AI lab who is passionate about agentic AI - systems where models reason, act, and learn autonomously. You should have a proven track record of building scalable, production-grade AI systems and a strong grasp of how to translate cutting-edge research into real-world impact. The ideal candidate combines deep technical expertise with creativity and a bias for shipping practical, elegant solutions.
Your role sits at the intersection of our data and backend teams. You will design and implement advanced, (multi-)agentic AI systems that apply LLMs not just as tools, but as autonomous collaborators - reasoning over data, orchestrating workflows, and driving decisions. Youβll combine solid backend engineering with a deep understanding of how LLMs can act, learn, and adapt to solve complex user problems at scale.
This role is perfect for someone who loves turning cutting-edge AI and NLP research into scalable systems, thrives on end-to-end ownership and autonomy, an experimentation-welcoming setting, and wants to shape how agentic AI transforms enterprise software.
You will be working closely with the Head of Agentic AI Engineering and our compact high-performance team of LLM engineers, software engineers, and data scientists. The team is part of recently acquired Berlin startup Kodex AI and works hybrid from an amazing office (great location, gym, rooftop pool & sauna, many events), and from home.
Our evolving tech stack:
Core: python (fastAPI, langchain), Typescript (React)
Infra & storage: MySQL, Pinecone, GCP, AWS, Azure, Firebase, Docker, github
Qualifications:
4+ years of experience in software or LLM engineering, ideally with Python
Strong foundation in backend or data systems, and experience deploying LLM-based applications to production
Familiarity with LLM orchestration frameworks (e.g. LangChain, LlamaIndex, OpenDevin, or custom agentic architectures)
Understanding of prompt engineering, retrieval-augmented generation (RAG), tool-use / agent frameworks, LLM evaluation, NLP methods
Experience with most of our tech stack (as listed above)
Bonus: experience building B2B SaaS or AI workflow products
Bonus: experience in an early-stage startup environment
Bonus: experience in FinTech / RegTech / Finance / Regulatory / Compliance domains
Great problem-solving skills, a pragmatic mindset, and a bias toward fast iteration
Curiosity and ability to learn new technologies quickly
Strong English communication skills and comfort working in a small, startup-like, tech-driven team
Interested?
If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.β
CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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Candidate Selection & Onboarding Process
Application & Resume Screening
Submit your tailored CV/Resume directly to the talent acquisition portal.
Technical & Competency Interviews
Virtual interviews with the hiring manager and multidisciplinary team.
Formal Offer & Benefits Negotiation
Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.
Onboarding & Corporate Integration
Equipment provisioning, team orientation, and commencement of duties.
United Kingdom Right to Work & Skilled Worker Visa Guide
Employment in the United Kingdom requires legal Right to Work verified under the Home Office Points-Based Immigration System:
Sponsoring employers must hold an active Home Office A-rated Sponsor License and assign a valid Certificate of Sponsorship (CoS). Role must meet the general minimum salary threshold (Β£38,700) or occupation going rate.
Continuous employment under Skilled Worker status establishes eligibility for Indefinite Leave to Remain (ILR) after 5 continuous years, leading to British Citizenship.
Candidate Preparation Blueprint: Technology
Based on transatlantic hiring benchmarks for Senior Agentic AI Engineer roles across Cube's corporate sector, successful applicants typically excel across three core dimensions:
Demonstrated portfolio evidence, architecture/system design case studies, or validated professional certifications directly applicable to Technology.
STAR method competency responses highlighting cross-functional leadership, conflict resolution, and delivering measurable enterprise ROI under tight timelines.
Total compensation expectation aligned within the benchmarked Salary Disclosed on Application bracket, including retirement vesting and health parity.
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