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# AI Solution Architect

- **Company:** NTT DATA Österreich GmbH
- **Location:** Austria (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Information Technology Consulting, Data Infrastructure, Software Engineering
- **Published:** August 5, 2026
- **Apply:** https://career5.successfactors.eu/careers?company=nttdatade&site=&career_ns=job_application&login_ns=register&career_job_req_id=22091

## About the Role

* 8+ years of experience in solution architecture, technology consulting, software engineering, data engineering, systems integration, presales, or delivery roles.
 * 3+ years of experience designing or delivering AI, data, analytics, ML, GenAI, agentic AI, or automation solutions.
 * 1+ year of hands-on or solutioning experience with GenAI, LLMs, RAG, AI agents, or enterprise AI platforms.
 * Experience producing solution blueprints, work estimates, delivery plans, staffing models, assumptions, dependencies, SOW inputs, and pricing or commercial inputs.
 * Working knowledge of cloud, data, integration, application architecture, security, responsible AI, governance, and operational support considerations.
 * Bachelor's degree or equivalent work experience.
 * Fluency in German and English

Preferred Skills:

 * Experience with Azure, AWS, GCP, OpenAI, Anthropic, Mistral, Google/Gemini, Databricks, Snowflake, vector databases, orchestration frameworks, and MLOps/LLMOps tooling.
 * Experience supporting large pursuits, proposal development, pricing reviews, or delivery mobilization.
 * AI/ML, cloud, data platform, architecture, or security certifications.
 * Strong analytical thinking, commercial judgment, written communication, cross-functional collaboration, and client-facing presentation skills.
 * Ability to travel as required for client and internal engagements.

## Description

* Design AI solutions aligned to client requirements, NTT DATA standards, and delivery capabilities.
 * Define scope, approach, solution blueprints, technical architectures, assumptions, dependencies, risks, and success criteria.
 * Build work estimates across roles, effort, skills, locations, tooling, platforms, and delivery dependencies.
 * Define workplan timelines, delivery phases, milestones, and MVP-to-scale implementation paths.
 * Partner with delivery, finance, and commercial teams to shape pricing inputs, deal economics, margin assumptions, and commercial options.
 * Support SOW development by defining scope boundaries, deliverables, acceptance criteria, dependencies, and change-control considerations.
 * Validate feasibility, implementation approach, resourcing model, integration complexity, data readiness, security, governance, and operational support requirements.
 * Incorporate partner platforms and models into solution designs where relevant.
 * Support technical Q&A, client demos, solution walkthroughs, proposal defense, and transition from pursuit to delivery.
 * Contribute reusable estimates, patterns, BOMs, workplans, solution artifacts, and lessons learned into the global AI GTM knowledge base.

Success Measures:

 * Pursuit deal volume, measured as total TCV value of AI deals where the AI Solution Architect supported.
 * Pursuit win rate for AI deals where the AI Solution Architect supported.
 * Utilization or billability against target.
 * Estimate quality, solution feasibility, commercial accuracy, and successful handoff into delivery.


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