AI Solution Architect

We are looking for an experienced AI Solution Architect to design and lead the architecture of scalable, secure, and production-ready AI solutions. The candidate will work with business stakeholders, product managers, data scientists, AI/ML engineers, software engineers, and cloud teams to transform business requirements into enterprise-grade AI architectures.

Key Responsibilities

• Design end-to-end architectures for AI, Machine Learning, Generative AI, and LLM-based solutions.
• Analyze business and technical requirements and translate them into scalable solution architectures.
• Define architecture patterns for AI applications, data platforms, APIs, microservices, and cloud infrastructure.
• Design enterprise Generative AI and LLM solutions, including RAG, vector databases, embeddings, prompt engineering, and model integration.
• Evaluate and recommend appropriate AI/ML models, frameworks, platforms, and technologies.
• Design data pipelines and integration architectures required for AI solutions.
• Define integration patterns between AI services and existing enterprise applications.
• Collaborate with engineering and data teams to ensure architecture feasibility and implementation.
• Establish standards for scalability, performance, availability, security, and maintainability.
• Design AI solutions across cloud platforms such as AWS, Azure, and Google Cloud.
• Provide technical leadership during development, testing, deployment, and production implementation.
• Review technical designs, code architecture, APIs, infrastructure, and AI/ML implementation approaches.
• Support MLOps and CI/CD architecture for model development and deployment.
• Define AI governance, security, privacy, compliance, and responsible AI considerations.
• Conduct technical assessments, proof-of-concepts, and architecture reviews.
• Identify technical risks, dependencies, bottlenecks, and opportunities for optimization.
• Create architecture diagrams, technical specifications, solution proposals, and documentation.
• Communicate complex technical concepts to both technical and business stakeholders.

Required Skills

• 8+ years of experience in software, cloud, data, or solution architecture.
• Strong hands-on understanding of AI/ML and Generative AI technologies.
• Strong knowledge of LLMs, RAG, embeddings, vector databases, prompt engineering, and AI application architecture.
• Experience with Python and AI/ML frameworks.
• Strong knowledge of APIs, microservices, distributed systems, and cloud architecture.
• Experience with AWS, Azure, or Google Cloud.
• Understanding of data engineering, data lakes, databases, and data integration.
• Knowledge of MLOps, CI/CD, Docker, Kubernetes, and infrastructure automation.
• Strong understanding of security, identity, access management, and enterprise architecture.
• Excellent architecture documentation and communication skills.

Preferred Qualifications

• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent platforms.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, or Azure AI Search.
• Experience implementing enterprise RAG and agentic AI solutions.
• Knowledge of AI model evaluation, observability, governance, and responsible AI.
• Cloud architecture certification such as AWS Solutions Architect, Azure Solutions Architect, or Google Cloud Architect.
• Experience working with enterprise clients and large-scale production environments.

Soft Skills

• Strong technical leadership and architectural decision-making.
• Excellent communication and presentation skills.
• Strong analytical and problem-solving capabilities.
• Ability to work with both business and technical stakeholders.
• Ability to translate complex business requirements into practical technical solutions.