[Hiring] AI Solution Architect @Marlabs

Role Description

As an AI Solution Architect, you are responsible for designing and shaping intelligent, scalable, and secure AI-driven solutions that align with business objectives and long-term technology strategy. You bring deep expertise in AI/ML architectures, data platforms, and cloud-native technologies, combined with strong consulting, communication, and stakeholder engagement skills. You serve as a trusted technical advisor, translating complex AI capabilities into clear, actionable business outcomes for clients and internal teams. As a strategic thinker, you balance innovation with practicality, ensuring solutions are robust, governable, and future-proof. You thrive in collaborative, fast-paced environments, guiding cross-functional teams while setting architectural standards and best practices that enable successful AI adoption at scale.

Qualifications

• 10+ years of experience in solution architecture, technical consulting, or engineering roles focused on data, analytics, and AI-enabled systems.
• 5+ years of hands-on experience designing and implementing AI/ML solutions using modern cloud platforms (e.g., Azure, AWS, GCP) and AI services.
• Strong expertise in data architectures, including data lakes, lakehouses, data warehouses, and real-time or event-driven data platforms.
• Proven experience with AI/ML frameworks, model lifecycle management (MLOps), and scalable deployment patterns.
• Demonstrated ability to lead technical design discussions, influence architectural decisions, and communicate complex concepts to technical and non-technical audiences.
• Experience collaborating with delivery, product, and business teams to ensure solutions are feasible, secure, and aligned with strategic goals.
• Preferred certifications: Cloud Architect certifications (Azure, AWS, GCP), AI/ML certifications, TOGAF, or equivalent architecture credentials.

Requirements

• Lead the end-to-end design of AI and data solutions, ensuring alignment with business requirements, technical standards, and enterprise architecture.
• Act as the primary technical authority for AI initiatives, guiding solution decisions, managing architectural risks, and ensuring design integrity across delivery teams.
• Define and evolve AI architectures, including data pipelines, ML platforms, model deployment patterns, and integration with enterprise systems.
• Partner with clients and stakeholders to identify AI use cases, assess feasibility, and translate business needs into scalable technical solutions.
• Establish architectural governance, best practices, and design patterns to ensure security, compliance, performance, and maintainability.
• Provide hands-on technical guidance and mentorship to engineering teams during implementation, reviews, and production readiness.