Description

Key Responsibilities •             Define end-to-end architecture for enterprise AI and GenAI solutions. •             Establish reference architectures and reusable patterns for LLM, SLM, RAG, agentic AI, and traditional ML solutions. •             Evaluate AI models and platforms based on business requirements, accuracy, latency, security, scalability, and cost. •             Define criteria for determining when to use AI, what type of AI to use, and when traditional technology or automation is more appropriate. •             Develop strategies for model routing, token optimization, caching, prompt optimization, and inference-cost management. •             Architect secure integration of AI solutions with enterprise applications, APIs, data platforms, and knowledge repositories. •             Provide architecture guidance for AI agents, orchestration, vector databases, embeddings, APIs, and model gateways. •             Collaborate with security, data, infrastructure, governance, and application architecture teams. •             Provide technical leadership to engineering teams and conduct architecture/design reviews. •             Help translate business use cases into scalable AI solution architectures. Required Skills •             Strong enterprise solution architecture experience with significant exposure to AI/ML and GenAI. •             Hands-on understanding of LLMs, SLMs, RAG, embeddings, vector databases, AI agents, prompt engineering, and model evaluation. •             Experience with cloud AI platforms such as Azure AI, AWS, or Google Cloud. •             Understanding of commercial and open-source AI models. •             Strong knowledge of APIs, microservices, containers, cloud architecture, security, and enterprise integration. •             Ability to evaluate architectural trade-offs across quality, performance, risk, scalability, and cost. Preferred Experience •             10+ years in IT/data analytics, with 5+ to 7+ years specifically focused on designing and deploying enterprise AI/ML solutions. •             12+ years in technology with substantial architecture experience. •             Experience architecting enterprise-grade GenAI solutions. •             Experience in financial services or another highly regulated industry is preferred

Key Skills

Education

Bachelor’s degree