AI Solutions Architect
AI Solutions Architect – Enterprise AI Platform (Agents, Workflows, Governance)Role OverviewWe are seeking an experienced AI Solution Architect to lead the design and implementation of enterprise-level AI solutions. In this role, you’ll bridge the gap between business needs and technical capabilities, architecting scalable AI systems that deliver measurable business value while guiding technical teams through complex AI implementations. Primary ResponsibilitiesAs an AI Solution Architect you: Design end-to-end AI solution architectures that align with business objectives and technical requirementsEvaluate business challenges and identify opportunities where AI can provide effective solutionsLead technical discussions with stakeholders to translate business problems into AI-driven solutionsDefine technical standards, best practices, and architectural patterns for AI projectsOversee the integration of AI solutions with existing enterprise systems and infrastructureCollaborate with data scientists, engineers, and business teams to ensure successful project deliveryConduct feasibility studies and proof-of-concepts for new AI initiativesCreate technical documentation, architecture diagrams, and implementation roadmapsProvide technical leadership and mentorship to development teamsStay current with emerging AI technologies and assess their potential business applicationsEnsure AI solutions meet security, scalability, performance, and compliance requirements Technical ExpertiseAI/ML Technologies: Deep learning, NLP, computer vision, reinforcement learning, generative AI (LLMs, diffusion models)Cloud Platforms: AWS (SageMaker, Bedrock), Azure (AI Services, OpenAI), GCP (Vertex AI)Data Technologies: SQL/NoSQL databases, data warehouses, data lakes, streaming platformsMLOps Tools: MLflow, Kubeflow, DVC, model registriesArchitecture: Microservices, API design, event-driven architectures, serverlessProgramming: Python, understanding of other languages (Java, Scala, etc.)Containerization: Docker, KubernetesIntegration: REST APIs, message queues, ETL/ELT pipelinesRequired Qualifications (Hard Requirements)Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)5+ years of experience in solution architecture, with at least 3 years focused on AI/ML projectsProven ability to identify, analyze, and solve complex business problems using AI technologiesStrong track record of architecting and delivering AI solutions that address real-world challengesDeep understanding of AI/ML technologies, including traditional ML, deep learning, and generative AIExperience designing scalable, production-ready AI systemsStrong knowledge of cloud architectures (AWS, Azure, or GCP) and AI/ML servicesExpertise in data architecture, data pipelines, and data governance