Senior AI Solution Architect

Excerpt from the original posting

Job Summary
We are seeking an experienced AI Solution Architect with 8–10 years of experience in Artificial Intelligence (AI), Machine Learning (ML), and enterprise solution architecture. The ideal candidate will be responsible for designing, developing, and implementing scalable, secure, and high-performance AI solutions aligned with business objectives.
The candidate should have strong expertise in AI/ML architecture, Generative AI, Large Language Models (LLMs), cloud-based AI platforms, and enterprise system integration. The role requires close collaboration with business stakeholders, data scientists, software engineers, and technology teams to translate business requirements into effective AI-driven solutions.
Key Responsibilities
- Design end-to-end AI/ML solution architectures aligned with business requirements and enterprise technology standards.
- Define AI strategy, architecture patterns, technology stacks, and implementation roadmaps.
- Architect and implement AI, ML, Generative AI, and LLM-based solutions for enterprise use cases.
- Design Retrieval-Augmented Generation (RAG) architectures, vector database integrations, and knowledge retrieval pipelines.
- Evaluate and select appropriate AI models, frameworks, platforms, and cloud services based on business and technical requirements.
- Develop architecture for scalable AI applications, APIs, microservices, and enterprise integrations.
- Design and implement AI solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Establish best practices for model deployment, monitoring, versioning, performance optimization, and lifecycle management using MLOps principles.
- Define responsible AI practices, including data privacy, security, explainability, bias mitigation, and governance.
- Assess the feasibility, scalability, cost, and business value of proposed AI solutions.
- Collaborate with data scientists, ML engineers, data engineers, developers, and business stakeholders throughout the solution lifecycle.
- Develop architecture diagrams, technical specifications, proof of concepts (POCs), and implementation plans.
- Guide development teams on AI architecture, coding standards, integration patterns, and deployment practices.
- Monitor emerging AI technologies and recommend innovations that improve business outcomes.
- Ensure AI solutions meet enterprise security, compliance, performance, availability, and reliability requirements.
Required Skills and Qualifications
- 8–10 year…

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