Senior AI Solution Architect

Key Responsibilities 

• Design and architect end-to-end enterprise AI solutions covering data ingestion, model deployment, API orchestration, system integration, and AI platform services across hybrid cloud and on-premise environments.
• Develop scalable AI solution architectures by translating business requirements into technical blueprints, selecting appropriate AI frameworks, cloud platforms, and enterprise technologies.
• Lead the integration of AI capabilities, including LLMs, Agentic AI, RAG solutions, AI Workbenches, and Model Management platforms with enterprise applications and business systems.
• Establish secure, scalable, and compliant AI architectures by embedding cybersecurity, data governance, privacy, and enterprise compliance requirements into solution designs.
• Evaluate, recommend, and implement AI platforms, cloud services, open-source technologies, and vendor solutions to support enterprise AI initiatives.
• Collaborate with AI Engineers, Data Engineers, Platform Engineers, and business stakeholders to operationalize AI solutions, ensuring scalability, reliability, and lifecycle management.
• Lead technical solutioning, proof-of-concepts (PoCs), architecture reviews, and innovation initiatives while mentoring a small team of AI engineers and application developers.
• Define architectural standards, reusable design patterns, and AI best practices while continuously evaluating emerging technologies to drive enterprise AI innovation.

Key Requirements 

• Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Data Science, or a related discipline.
• 5+ years of experience in Solution Architecture with strong expertise in AI/ML platforms, enterprise integration, cloud-native applications, and API-driven architectures.
• Proven experience designing enterprise AI solutions involving data pipelines, model orchestration, LLMs, Agentic AI, RAG, and AI platform architectures.
• Hands-on experience with cloud AI platforms such as Microsoft Azure AI/ML, Azure AI Foundry, AWS SageMaker, AWS Bedrock, or equivalent AI cloud services.
• Strong knowledge of AI frameworks and orchestration technologies including LangChain, LangGraph, GraphRAG, Kubeflow, Ray, MCP, and modern AI development tools.
• Experience designing secure, scalable APIs, integrating enterprise systems, and implementing AI governance, security, and compliance best practices.
• Excellent stakeholder management, technical leadership, communication, and presentation skills with the ability to bridge business and technical teams.
• Strong problem-solving mindset with experience leading architecture reviews, evaluating emerging AI technologies, mentoring technical teams, and delivering enterprise-scale AI transformation projects.