AI Architect, AI Development

About This Role

The AI Architect is the technical authority on Insight's AI Development team, responsible for defining the architectural blueprints, patterns, and standards that guide how AI solutions are designed, built, and deployed across the enterprise. You will work across multiple projects simultaneously, ensuring consistency, scalability, and security whether the team is building a conversational AI agent, a RAG-powered search tool, or an intelligent automation workflow. This role combines deep technical expertise with cross-functional leadership and mentorship.

Key Responsibilities

• Define and maintain the architectural standards, design patterns, and best practices for AI application development across the team.

• Design end-to-end solution architectures for AI initiatives, including model integration, data flows, API design, security, and cloud infrastructure.

• Evaluate and recommend AI technologies, frameworks, and cloud services (Azure AI Foundry, Semantic Kernel, Databricks, etc.) for adoption.

• Conduct architectural reviews, design sessions, and code reviews to ensure quality, security, and alignment with enterprise standards.

• Partner with Platform Engineers and DevOps to define infrastructure requirements, IaC standards, and deployment patterns.

• Collaborate with Product Owners, Data Engineers, and business stakeholders to translate business requirements into scalable technical solutions.

• Mentor and coach engineers across the team, fostering a culture of technical excellence and continuous learning.

• Stay current with emerging AI technologies and advise leadership on strategic technology direction.

Qualifications

• Experience: Minimum 5 years of experience in software engineering, with at least 2 years in a solutions or application architecture role involving AI/ML or data-intensive applications.

• AI/ML: Strong understanding of LLM-based application architectures, including prompt engineering, RAG, agent orchestration, embeddings, and vector databases.

• Cloud: Deep expertise in Microsoft Azure (Azure AI Foundry, Azure OpenAI, App Services, Entra). Familiarity with Google Cloud Platform (Vertex AI) is a plus.

• Data: Experience with Databricks and data lakehouse architectures.

• Programming: Proficiency in Python; familiarity with JavaScript/React for full-stack context.

• Infrastructure: Experience with Infrastructure as Code (Terraform, Bicep) and CI/CD pipeline design.

• Leadership: Excellent communication skills; proven ability to lead technical teams and articulate complex concepts to both technical and non-technical audiences.

• Nice to Have: Experience with Semantic Kernel, on-premises model hosting, or model fine-tuning/evaluation.