- Design and implement end-to-end generative AI solution architectures that meet business requirements and adhere to industry best practices.
• Translate complex business challenges into scalable, secure, and cost-efficient architectures leveraging generative AI technologies.
• Evaluate and select appropriate frameworks and architectural patterns to ensure performance, scalability, and maintainability.
• Develop prototypes and proof-of-concepts to validate architectural decisions and demonstrate business value.
• Ensure AI solutions comply with ethical standards, governance frameworks, and regulatory requirements, embedding responsible AI practices into the
architecture.
- Provide technical leadership and mentorship to engineering and data science teams, ensuring alignment with architectural principles.
• Stay abreast of emerging trends in GenAI design patterns, agentic frameworks, orchestration tools, and MCP (Model Context Protocol) to inform strategic
and architectural decisions.
• Communicate complex architectural concepts to technical and non-technical stakeholders effectively.
Mandatory Skills
- Generative AI architecture knowledge, including design patterns, solution blueprints, and best practices for enterprise adoption.
• Expertise in cloud platforms (especially AWS) with experience designing solutions using services such s SageMaker, Bedrock, vector databases, etc.
• Familiarity with MCP (Model Context Protocol) and its role in extensible, standardized agentic systems.
• Strong ability to assess, select, and integrate generative AI models, orchestration frameworks, and agentic approaches into enterprise solutions.
• Proven experience in solution architecture, with the ability to design system integrations, APIs, data pipelines, and deployment strategies around GenAI.
• Strong stakeholder management skills, with the ability to challenge and influence diverse audiences to align on architectural direction.
• Awareness of ethical considerations, governance frameworks, and responsible AI design, especially in generative use cases.
Nice to Have Skills
- Experience with enterprise architecture frameworks (TOGAF, Zachman, etc.) and applying them to AI/ML solutions.
Experience
• Minimum 5 years in AI/ML solution architecture, with at least 1 year focused on generative AI solution design and delivery.
• Proven track record designing and delivering enterprise-grade AI systems on AWS or other major cloud platforms.
Qualifications
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Relevant certifications (e.g., AWS Certified Solutions Architect, AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer) are a plus.
- Liderazgo técnico y capacidad de gestión de equipos.
- Excelentes habilidades de comunicación y presentación.
- Pensamiento estratégico y orientación a resultados.
- Capacidad para trabajar en entornos dinámicos y con múltiples interlocutores.
Inetum is a European leader in digital services. With a team of 28,000 consultants and specialists, Inetum works every day to create digital impact for businesses, public sector organizations, and society as a whole. The company’s solutions are designed to boost both client performance and innovation, while also contributing to the common good.
Present in 19 countries with a strong network of local offices, Inetum partners with leading software providers to address the challenges of digital transformation with proximity and flexibility.
Originally posted on Himalayas