Artificial Intelligence Architect

You will serve as a senior technical leader responsible for driving the adoption and delivery of innovative AI capabilities across the organization. This is a hands-on individual contributor role where you'll combine deep software engineering expertise with advanced AI knowledge to build intelligent, scalable solutions that support critical business operations.

Working alongside executive technology stakeholders, you'll influence long-term architecture decisions, champion engineering excellence, and help establish the standards, frameworks, and governance practices required to deliver AI safely and effectively in a highly regulated environment.

Key Responsibilities

• Partner with senior AI leadership to define and execute the organization's AI architecture vision, technology roadmap, and adoption strategy.
• Design and deliver enterprise-scale AI solutions that integrate intelligent agents, large language models, data platforms, and business-critical applications.
• Architect and develop production-grade AI applications within AWS environments, ensuring solutions are secure, scalable, resilient, and aligned with enterprise standards.
• Establish architecture patterns, governance frameworks, and technical controls that address AI risks including hallucinations, bias, data privacy, prompt security, and output validation.
• Provide technical leadership across AI initiatives through architecture reviews, solution design guidance, code reviews, and the promotion of modern engineering best practices.
• Evaluate emerging AI technologies, models, and frameworks to identify opportunities for innovation while helping shape the organization's long-term AI strategy.

Technical Skills

• Strong background designing and delivering AI, machine learning, and generative AI solutions, with expertise in solution architecture and enterprise system integration.
• Expert-level Python skills and strong SQL experience, with the ability to translate architectural designs into production-ready solutions when required.
• Hands-on experience with large language models, agentic AI frameworks, and modern AI application patterns, including RAG, orchestration, and model integration.
• Experience architecting cloud-native solutions within AWS and working with Docker, Kubernetes, and CI/CD pipelines to support scalable AI platform delivery.
• Strong understanding of data engineering principles, including data pipelines, transformation frameworks, data modelling, and enterprise data architecture.
• Deep knowledge of AI governance, responsible AI practices, and risk management, including hallucinations, prompt injection, bias mitigation, data privacy, auditability, and output assurance.
• Experience evaluating and leveraging leading AI models and tools, including Claude and other emerging technologies, to drive innovation and improve solution design.