MSX International
Automotive
AISolutionsArchitect
“AI Solutions Architect at MSX International. Skills: AI Solutions Architecture, Machine Learning, Generative AI, Technical Design, Scalability, Cost-Efficiency, Reliability. Designing scalable, secure, and high-performance blueprints. Bridging the gap between high-level business requirements and AI engineering execution”
What You'll Achieve.
AI solutions successfully deployed from concept to production; Scalable, reusable architecture patterns adopted across the enterprise; Optimized cost, performance, and reliability of AI systems; alignment between business needs, engineering delivery, and governance requirements
Industry & Context.
technical feasibility evaluation; rapid prototyping; POCs; MVPs; assess cost impact; optimize architectures
What They're Looking For.
Must Have
Bachelor’s or Master’s Degree in Computer Science, Data Science, Software Engineering, or a related quantitative field, Solid foundational knowledge in Machine Learning and Software Architecture, 5+ years of significant experience in designing end-to-end technical architectures for Machine Learning and Generative AI solutions, Proven track record in conducting technical feasibility assessments, rapid prototyping (POCs/MVPs), and bridging business requirements with engineering execution, Experience with enterprise-scale systems, security standards, and AI governance, Expertise in AI design patterns (such as RAG, Fine-tuning, and Agentic workflows) and model evaluation frameworks, technical leadership and mentorship abilities, exceptional stakeholder management across cross-functional teams (Security, Data, Infrastructure), the capability to optimize architectures for scalability, cost-efficiency, and reliability, Professional proficiency in English
Nice to Have
Italian and/or additional European languages are a plus
What You'll Do.
and high-performance blueprints
Bridging the gap between high-level business requirements and AI engineering execution
Evaluating AI-related initiatives from a technical perspective
Architecting for value
scaling and long-term sustainability
feasibility evaluation
and architectural integrity
Recommending reference architectures for AI related solutions
Designing end-to-end pipelines for Generative AI
and Agentic workflows
Ensuring AI solutions are modular
and aligned with enterprise security and compliance standards
Recommending the optimal technical stack for specific business use cases
Partnering with AI & Data Governance to ensure architectures align with risk
and lifecycle requirements
Conducting evaluation of the technical feasibility of AI related initiatives
Conducting rapid prototyping
to validate AI-specific technical assumptions
Supporting defining technical requirements
and integration points for AI related initiatives
Collaborating with Security
and Infrastructure teams to validate architectural assumptions and verify technical fit
Providing high-level effort estimations and resource requirements for AI implementations
Supporting defining what AI models need to move beyond "lab" environments into robust
scalable production systems
Supporting defining requirements for scaling
Recommending optimized architectures for latency
cost-efficiency (token management)
Assessing cost impact of model choices
and orchestration designs
Establishing patterns for AI safety
and "Human-in-the-loop" architectural components
Acting as the "North Star" for tech people involved in the implementation of AI related solutions
Providing technical oversight and architecture reviews for AI related projects
Monitoring emerging AI patterns (RAG
Collaborating with the AI & Data Transformation Lead to support Value Streams and Support Functions on advisory support for AI uses cases
Maintaining and evolving a set of reusable AI architecture patterns and component templates
Designing and executing the technical assessment of AI models
and emerging technologies
Applying structured LLM validation frameworks to assess model performance
and technical suitability
Reviewing external AI products and services from a technical perspective
Staying at the forefront of AI research to identify and integrate new technical capabilities
Ensuring AI related solutions maintain technical flexibility and avoid architectural lock-in
Maintaining concise architectural documentation
How You'll Work.
Team & Collaboration
Partner with AI & Data Governance; Collaborate with Security, Data, and Infrastructure teams; Collaborate with the AI & Data Transformation Lead; stakeholder management across cross-functional teams (Security, Data, Infrastructure)
Communication Scope
Professional proficiency in English
Process & Methodology
high-level effort estimations, resource requirements
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