Role: AI Solution Architect Skills: Core AI & GenAI, Architecture & Design, LLM‑driven workflows, agentic frameworks, API, Cloud Platforms
The AI architect will define end‑to‑end agent frameworks, ensure alignment with available enterprise environment, guardrails, and partner closely with engineering, QE, security, and compliance teams.
Partner with senior stakeholders to identify high‑impact use cases (automation, decision support, quality, operations).
Provide executive‑level guidance on agentic AI adoption, maturity models, and roadmaps.
Define reference architectures for agentic AI systems (single‑agent, multi‑agent, hierarchical, tool‑using agents).
Architect RAG‑based and tool‑augmented agents using enterprise data sources, APIs, and workflows.
Ensure scalability, resilience, observability, and cost optimization of agent platforms.
Governance, Risk & Guardrails
Establish AI guardrails covering safety, bias, explainability, auditability, and regulatory compliance.
Define agent lifecycle management (design, testing, deployment, monitoring, retirement).
Partner with Risk, Legal, Security, and QE teams to ensure model risk management (MRM) and enterprise readiness.
Core AI & GenAI
Strong understanding of RAG, embeddings, vector databases, and knowledge grounding.
Strong background in distributed systems, APIs, microservices, and cloud‑native architectures.
Proficiency in Python and familiarity with enterprise integration patterns.
Experience with cloud platforms (Azure, AWS, GCP) and secure enterprise deployments.
Knowledge of observability, monitoring, and cost management for AI systems.
The AI architect will define end‑to‑end agent frameworks, ensure alignment with available enterprise environment, guardrails, and partner closely with engineering, QE, security, and compliance teams.
Partner with senior stakeholders to identify high‑impact use cases (automation, decision support, quality, operations).
Provide executive‑level guidance on agentic AI adoption, maturity models, and roadmaps.
Define reference architectures for agentic AI systems (single‑agent, multi‑agent, hierarchical, tool‑using agents).
Architect RAG‑based and tool‑augmented agents using enterprise data sources, APIs, and workflows.
Ensure scalability, resilience, observability, and cost optimization of agent platforms.
Governance, Risk & Guardrails
Establish AI guardrails covering safety, bias, explainability, auditability, and regulatory compliance.
Define agent lifecycle management (design, testing, deployment, monitoring, retirement).
Partner with Risk, Legal, Security, and QE teams to ensure model risk management (MRM) and enterprise readiness.
Core AI & GenAI
Strong understanding of RAG, embeddings, vector databases, and knowledge grounding.
Strong background in distributed systems, APIs, microservices, and cloud‑native architectures.
Proficiency in Python and familiarity with enterprise integration patterns.
Experience with cloud platforms (Azure, AWS, GCP) and secure enterprise deployments.
Knowledge of observability, monitoring, and cost management for AI systems.
AI Solution Architect (Chicago) in chicago at Unknown Company
This position is listed as full time and onsite.