Job Description We are seeking a hands-on Principal AI Solutions Architect to help define, design, and build the next generation of our enterprise AI platform. This individual will serve as the bridge between business vision and technical execution, translating complex business requirements into scalable AI and machine learning solutions. This is not a traditional Enterprise Architect or management consulting role. We are looking for a builder—someone with deep expertise in Generative AI, Agentic AI architectures, machine learning, and cloud-native engineering who can architect solutions while remaining actively involved in prototyping and implementation. The ideal candidate has experience designing and deploying enterprise-scale AI platforms, understands how to leverage modern AWS AI services, and can guide teams from concept through production. AI Platform Strategy & Architecture

•  Design and evolve the enterprise Agentic AI platform strategy.
•  Translate business challenges and opportunities into scalable AI solution architectures.
•  Create technical roadmaps that move initiatives from concept to production.
•  Define architectural standards, governance models, and best practices for AI implementations.
•  Partner with enterprise technology leaders, product teams, and business stakeholders to align AI investments with business outcomes. Agentic AI & Generative AI Solutions
•  Architect and implement autonomous agent frameworks and multi-agent systems.
•  Design Agentic workflows capable of planning, reasoning, orchestration, tool usage, and workflow automation.
•  Evaluate and integrate foundation models, LLMs, and emerging AI technologies.
•  Lead implementation of Retrieval-Augmented Generation (RAG), agent memory architectures, vector databases, and model orchestration frameworks.
•  Define approaches for prompt engineering, evaluation, observability, and AI governance. Hands-On Engineering & Prototyping
•  Build proof-of-concepts and production-ready prototypes.
•  Collaborate directly with engineering teams on architecture implementation.
•  Provide technical leadership on software design patterns, APIs, integrations, and cloud-native AI services.
•  Troubleshoot architectural challenges and optimize AI solution performance.
•  Help establish reusable AI accelerators and reference architectures. Cloud & Machine Learning Architecture
•  Design scalable AWS-based AI infrastructure.
•  Leverage services such as: o Amazon Bedrock o Amazon SageMaker o AgentCore / Agent Services o Lambda o ECS/EKS o S3 o OpenSearch o EventBridge o Step Functions
•  Define MLOps and LLMOps frameworks for deployment, monitoring, retraining, and governance.
•  Optimize AI solutions for security, compliance, scalability, and cost efficiency.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

•  5-10+ years of software engineering, machine learning, automation and solution architecture experience.
•  5+ years designing cloud-native solutions in AWS.
•  Demonstrated experience designing enterprise AI/ML systems.
•  Strong understanding of Generative AI and Large Language Models.
•  Experience building Agentic AI solutions and orchestration frameworks.
•  Deep knowledge of: o Amazon Bedrock o AgentCore o SageMaker o RAG architectures o Vector databases o Prompt Engineering o LLM evaluation frameworks o Model deployment pipelines
•  Strong software engineering foundation with hands-on development experience in: o Python o APIs & Microservices o Cloud-native architectures
•  Ability to communicate effectively with both executive stakeholders and technical teams.
•  Experience translating business requirements into technical architectures and implementation plans.