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Senior Solution Architect – AI/ML/Data Architectures

Original title: Senior Solution Architect – AI-/ML-/Data-Architekturen_#3129_LP3628

Deloitte GmbH · Frankfurt am Main, Deutschland, Germany · Hybrid · Senior

  • Frankfurt am Main, Deutschland, Germany · Hybrid
  • 10 Monate
  • German

Indexed (2 weeks ago) · refreshed constantly

Start
2026-10
Duration
10 Monate
Work mode
Hybrid
Contract
Freelance / B2B
Seniority
Senior
Reference
3059053

Required skills

Nice to have:GenAIAI Program ManagementRegulated IndustriesTechnical FeasibilityCompliance

Languages: German

Job description

Seeking a Senior Solution Architect with expertise in AI, ML, and Data Architectures for a project focused on building GenAI competencies within a consulting environment. The role involves developing strategies, target states, and solution options for complex IT and data platforms.

Project overview

Application/Offer Deadline October 13, 2026, 2:00 PM

Contract Type: Service project. Clarify employment type/freelancer admissibility and supply chain before submission.

Bundle Request: 7/7

____

Project Framework Conditions

Project details

Frankfurt am Main; possibly other locations in Germany

October 19, 2026 – July 31, 2027; approx. 9.40 months

Scope: 30 PT of which 28 remote, 2 onsite = 93.33% remote

Utilization: Average approx. 0.73 days/week

Language: German native speaker C2

Onshore: Germany

Project Framework Conditions

October 19, 2026 – December 31, 2027; approx. 14.42 months

Utilization: Average approx. 0.48 days/week

Conditions – Mandatory Information for Candidates:

For further processing of your application, this information is mandatory: Please state your desired billing method and your hourly or daily rate, separated for remote and onsite. Also indicate whether travel expenses are included or charged separately. If charged separately, please state the amount or the basis for calculation.

1.1 Project/Process Context

Organization-wide development of GenAI competencies in the consulting environment: secure, compliant AI use, qualification, and practical use-case development. Interdisciplinary groups evaluate potentials and business cases, create implementation roadmaps, and permanently anchor AI competencies.

1.2 Project Structure

Central program management controls planning, goals, and communication. Sub-projects: Qualification/competence building and use-case identification/development. Cross-functional working groups with subject matter leadership; external specialists as needed. Sequential phases according to competence level with milestones; regular communication at management, steering, and operational levels.

3.1. Scope

Independent and self-organized: Analyze end-to-end integration and as-is/to-be architecture; develop strategies, target states, architecture models, and solution options. Document and communicate standard patterns/frameworks. Evaluate technical/business risks and recommend countermeasures. Check implementation against quality standards; support architecture development through reviews. Validate fit/gap analyses, prioritized measures, roadmaps, and principles. Conduct architecture/compliance reviews and technical due diligence under operational standards.

4.1 Must-Have Requirements - 100% mandatory to fulfill

4.2 Should-Have Requirements

  • Conditions / Billing Method (Hourly or Daily Rate)
  • Hourly Rate Remote (EUR/hour) and Hourly Rate Onsite (EUR/hour)
  • Or Daily Rate Remote (EUR/day) and Daily Rate Onsite (EUR/day)
  • Travel Expenses
  • M1: Experience in the conception and management of solution architectures for complex IT or data platforms — Senior (> 5 years of experience)
  • M2: Experience in the development of AI, ML, or Data Architectures including architectural decisions and technical target states — Senior (> 5 years of experience)
  • M3: For the following tender with project description, The program for qualification and transformation with generative AI has the following content: As part of an organization-wide qualification and transformation project, the use of generative AI is to be systematically [Incomplete: Text ends in original at "systematically"; professional content needs clarification.] — References: 2
  • M4: Experience in integrating solution architectures into existing IT and data landscapes, considering technical dependencies — References: 3
  • M5: Experience in implementing governance requirements within solution architectures — References: 3
  • S1: Demonstrable architectural responsibility in an AI program within a regulated infrastructure or network industry — References: 1 | 30%
  • S2: Experience in considering governance requirements in architectural decisions for AI or GenAI use cases — References: 1 | 20%
  • S3: Experience in evaluating the technical feasibility of AI or GenAI use cases from an architectural perspective — References: 1 | 20%
  • S4: Experience in architecturally evaluating regulatory, technical, or operational risks of AI solutions — References: 1 | 15%
  • S5: Experience with architecture documentation for AI solutions to meet proof and compliance requirements — References: 1 | 15%
  • Start: 2026-10
  • Duration: 10 Monate
  • Remote: hybrid
  • Location: Frankfurt am Main, Deutschland, DE
  • Languages: German

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