Principal AI Architect

🕒 July 27

🌽 Illinois – Remote

🌽 Illinois – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 18%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Paradigm

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1991

☁️ SaaS

💰 Private equity on 2025-08

SaaS

Paradigm is a company whose publicly accessible web application returned only the message: "Loading application... Your web browser must have JavaScript enabled in order for this application to display correctly. " No additional information about its products, services, or market focus was available from the provided content. Based on the presence of a web application but lacking further details, no definitive product, sector, or clientele can be determined from the supplied input.

📋 Description

• Architect and deliver end-to-end AI, Generative AI, and agentic AI solutions from concept through production • Apply hands-on expertise to build LLM-based systems, RAG pipelines, AI agents, and multi-agent orchestration solutions • Design AI platform capabilities including model selection, LLM routing, retrieval strategies, memory systems, and tool/function orchestration • Lead hands-on prototyping and proof-of-concepts to validate technologies and accelerate adoption • Ensure AI solutions are designed for performance, scalability, observability, privacy, and operational readiness • Define and drive architecture across multiple domains/business segments, ensuring alignment with enterprise strategy • Partner with business and technology leadership to shape AI roadmap, priorities, and execution strategy • Establish and promote architecture standards, reusable patterns, and best practices • Drive modernization initiatives to reduce technical debt and improve scalability, resilience, and performance • Implement and guide AI governance, security, responsible AI, and compliance practices • Ensure AI solutions are designed for performance, observability, privacy, and operational readiness • Collaborate across engineering, data, product, and business teams to deliver production-grade AI solutions • Mentor engineers and architects and effectively communicate AI concepts to technical and non-technical stakeholders.

🎯 Requirements

• 10+ years of experience in software engineering, architecture, and enterprise system design. • Proven experience delivering end-to-end AI/ML and Generative AI solutions in production environments. • Strong hands-on engineering capability with ability to operate across architecture, design, and implementation. • Deep expertise in LLMs, prompt engineering, RAG, embeddings, vector databases, and agent-based systems • Experience with agent frameworks and orchestration including multi-agent patterns and integrations • Strong programming experience in Python and building APIs, microservices, and distributed systems. • Experience designing and implementing solutions on cloud platforms (Azure preferred). • Experience with DevOps practices, including CI/CD, containerization, and scalable deployment of AI systems. • Familiarity with infrastructure-as-code (Terraform, Bicep) and Kubernetes-based deployments. • Strong understanding of data architecture and integration patterns supporting AI workloads. • Ability to evaluate emerging technologies and translate them into enterprise-scale capabilities • Solid knowledge of AI governance, risk, compliance, privacy, and responsible AI principles • Strong communication and stakeholder management skills. • Ability to influence decisions across engineering, data, and business teams. • Proven ability to mentor, guide, and elevate engineering and architecture teams. • Master’s or Bachelor’s degree in Computer Science, Engineering, Data Science, or a related STEM field.