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🤖ML Engineer

Solutions Architect

Deutsche Börse · Luxembourg, Prague, Frankfurt am Main
// classified as
ML Engineer (Productionizing models, serving, MLOps.)
posted
1d ago
location
Luxembourg, Prague, Frankfurt am Main
languages
python
tools
—
> stack
python
> education
masterms
> description

Your area of work:

As Solutions Architect, you bridge business strategy and engineering execution. You design and deliver enterprise solutions integrating AI and data platforms, translate vision into technical specifications, and ensure regulatory compliance.

Your responsibilities:

  • Develop and validate technical architecture: Decompose business requirements into detailed technical specifications and design trade-offs. Assess feasibility, validate assumptions with stakeholders, and ensure alignment between business goals and technical constraints.

  • Design system integrations and data governance: Architect end-to-end data flows across multiple systems. Define integration patterns, data models, APIs, and governance frameworks. Ensure data consistency, auditability, and regulatory compliance.

  • Establish governance and control frameworks: Design control mechanisms, audit trails, and compliance checkpoints. Ensure solutions meet industry standards and regulatory requirements. Document governance models and maintain compliance oversight.

  • Lead vendor and stakeholder management: Act as technical peer to solution integrators and infrastructure partners. Lead design reviews, negotiate technical trade-offs, and ensure delivery quality. Provide technical credibility in vendor negotiations.

  • Guide backlog refinement and story definition: Collaborate with program management to decompose initiatives into detailed technical stories. Define acceptance criteria, dependencies, requirements and identify risks early.

  • Drive technical alignment and decision-making: Coordinate architecture discussions across functions. Prepare technical analyses, architecture reviews, and proposals for senior management. Facilitate consensus on complex technical decisions.

  • Monitor performance and optimization: Identify system bottlenecks and performance issues. Recommend improvements and optimizations. Stay current with emerging technologies and industry best practices.

Your profile:

  • University degree in Computer Science, Software Engineering, Data Science, or equivalent technical discipline with strong academic results

  • Minimum 3–5 years' experience in technical architecture, systems integration, or technical program management

  • Minimum 2 years' hands-on experience with enterprise systems, AI/ML platforms, data pipelines, or cloud infrastructure

  • Track record delivering large-scale, multi-system transformations successfully

  • Enterprise architecture and systems design (distributed systems, cloud platforms, APIs, integrations)

  • AI/ML systems architecture and knowledge management

  • Data governance, data modeling, and master data management

  • Cloud platforms and modern infrastructure patterns

  • Regulatory frameworks (GDPR, SOC 2, COSO) and audit-ready system design

  • Agile delivery and technical backlog management

  • Strong problem-solving and analytical skills

  • Ability to translate business requirements into technical solutions

  • Vendor and stakeholder management with technical negotiation skills

  • Self-motivated, proactive, and reliable under pressure

  • Excellent communication skills across technical and business audiences

  • Team player with strong interpersonal skills

  • Advanced MS Office skills

  • Experience with financial services or regulated industries

  • Hands-on programming skills (Python, SQL)

  • Fluency in spoken and written English (mandatory)

  • German beneficial

Apply at Deutsche Börse →