AI Agentic Architect

AI Solutions Architect – Enterprise AI Platform (Agents, Workflows, Governance) Role Overview We 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 Responsibilities As an AI Solution Architect you: Design end-to-end AI solution architectures that align with business objectives and technical requirements Evaluate business challenges and identify opportunities where AI can provide effective solutions Lead technical discussions with stakeholders to translate business problems into AI-driven solutions Define technical standards, best practices, and architectural patterns for AI projects Oversee the integration of AI solutions with existing enterprise systems and infrastructure Collaborate with data scientists, engineers, and business teams to ensure successful project delivery Conduct feasibility studies and proof-of-concepts for new AI initiatives Create technical documentation, architecture diagrams, and implementation roadmaps Provide technical leadership and mentorship to development teams Stay current with emerging AI technologies and assess their potential business applications Ensure AI solutions meet security, scalability, performance, and compliance requirements Technical Expertise AI/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 platforms MLOps Tools: MLflow, Kubeflow, DVC, model registries Architecture: Microservices, API design, event-driven architectures, serverless Programming: Python, understanding of other languages (Java, Scala, etc.) Containerization: Docker, Kubernetes Integration: REST APIs, message queues, ETL/ELT pipelines Required 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 projects Proven ability to identify, analyze, and solve complex business problems using AI technologies Strong track record of architecting and delivering AI solutions that address real-world challenges Deep understanding of AI/ML technologies, including traditional ML, deep learning, and generative AI Experience designing scalable, production-ready AI systems Strong knowledge of cloud architectures (AWS, Azure, or GCP) and AI/ML services Expertise in data architecture, data pipelines, and data governance Show more Show less