AI Solution Architect

The AI Solution Architect will lead the architecture, design, and deployment of advanced AI capabilities within enterprise applications for a large organization. This role requires deep technical expertise in building AI and ML solutions, along with hands-on experience in Large Language Models (LLMs), agent-based solutions, and associated design patterns. The architect will collaborate with functional SMEs, IT teams, and Enterprise Architecture to deliver scalable, secure, and innovative AI solutions that align with business objectives.

Key Responsibilities

• Architect AI Solutions:Design and implement end-to-end AI/ML architectures for enterprise applications, including custom model development and integration.
• Collaborate Across Teams:Partner with functional SMEs, IT and Enterprise Architecture teams to ensure alignment with business goals and technology standards.
• Innovate with Emerging Tech:Apply knowledge of LLMs, AI agents and generative AI to create intelligent, context-aware solutions.
• Solution Design & Deployment:Guide development and deployment of AI models, APIs and cloud-native services into enterprise systems.
• Establish Best Practices:Define patterns, standards and governance for AI integration and lifecycle management.
• Performance & Optimization:Ensure AI solutions meet performance, reliability, and cost-efficiency goals.
• Mentorship & Enablement:Provide technical guidance and foster AI adoption across teams.

Qualifications

• Education:Bachelor s or master s degree in computer science, Data Science, AI/ML, or related field.
• Experience:
• 10+ years in IT architecture, solution design, or software developer roles.
• 3+ years of hands-on experience inbuilding AI and ML solutions, including model training, fine-tuning and deployment.
• Proven experience withLLMs, agent-based architecturesand associated design patterns.
• Expertise in cloud platforms (such as Azure, AWS, GCP) and AI services.
• Certifications:Preferred certifications in AI/ML and cloud architecture (e.g., Azure AI Engineer, Azure Solutions Architect, AWS Machine Learning Specialty).

Skills & Competencies

• Technical Skills:
• Strong understanding of AI/ML concepts, generative AI, LLMs and agent-based systems.
• LLM-based architecture patterns such as RAG, agentic workflows, conversational AI, multi-turn chat orchestration, content filtering, memory and associated trade-offs; evaluation frameworks including Responsible AI.
• Proficiency in Python, TensorFlow, PyTorch and modern AI frameworks.
• Familiarity with MLOps, CI/CD pipelines for AI solutions.
• Expertise in cloud-native architectures and services e.g., Azure, AWS, GCP, Serverless & Batch Compute: Azure Functions, AWS Lambda; AI Platforms such as Azure AI Studio, AWS Bedrock, Google Vertex AI
• Data retrieval and storage e.g., Vector database, NoSQL, Relational DB, Knowledge Graphs; Azure AI Search, Chunking strategies
• Soft Skills:
• Excellent communication and stakeholder management skills.
• Strong problem-solving and analytical thinking.
• Ability to influence and drive consensus across diverse teams.
• Adaptability and continuous learning mindset.