Principal AI Architect

AI EngineerMachine Learning EngineerFull TimeRemoteLeadTeam 1,001-5,000Since 1991Company SiteLinkedIn

Location

Illinois

Posted

7 days ago

Salary

0

Seniority

Lead

Job Description

Principal AI Architect

Paradigm

• 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.

Job 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.

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