Agentic AI Architect

York Solutions, LLC; Maplewood (MN); Hybrid; USD 180,000 - 240,000; Full time

Job summary

York Solutions, LLC is seeking an experienced Agentic AI Architect to set the architecture, standards, and operating model for enterprise agent systems that plan, reason, and act via secure interfaces. You will lead a cross-functional team, define reference designs for multi-agent workflows, memory, orchestration, and human oversight, and mentor teams on modern engineering.

The role accelerates automation and decision support by delivering scalable, reliable, and compliant agent services

Qualifications

• Master’s degree in CS, applied math, engineering, or a related field completed before start.
• At least 5 years in AI engineering with 2+ years in generative AI, AI-driven automation, or RPA.

Responsibilities

• Own reference architecture and roadmap for agentic AI across enterprise platforms.
• Lead cross-functional teams and communicate decisions to executives.
• Deliver production-grade agentic solutions with CI/CD, testing, rollback, and human-in-the-loop controls.
• Establish governance, safety, and compliance, including prompt-injection defenses and data handling.

Skills

Python proficiency

Cross-functional leadership

AI engineering

Communication to execs

Security/compliance awareness

Education

Master’s degree in CS/math/engineering

Tools

LangGraph

AWS Bedrock AgentCore

Azure AI Agent Service/AI Foundry

Mulesoft

SAP BTP

Airflow

Kafka/Kinesis

Job description

Location: St. Paul - preference for hybrid but open to remote

Interview Process: Teams - 2 rounds

Client is seeking a highly skilled and experienced Agentic AI Architect to set the architecture, standards, and operating model for enterprise agent systems that plan, reason, and act via secure interfaces. Lead a cross-functional team, define reference designs for multi-agent workflows, memory, orchestration, and human oversight, and mentor teams on modern engineering.

Accelerate automation and decision support by delivering scalable, reliable, and compliant agent services integrated with core platforms. Set evaluation and safety standards, partner with risk, security and compliance to ensure security, reliability & performance of Agentic solutions.

Key Responsibilities:

• Own the reference architecture and roadmap for agentic AI, defining standards for multi-agent patterns, tool/function interfaces, RAG/memory design, orchestration, security, and environment segregation.
• Translate business objectives into a prioritized portfolio of agentic use cases; mentor engineers and data scientists; and communicate architecture decisions, risks, and value realization to executive stakeholders.
• Lead the design and delivery of production grade agentic solutions that safely execute actions in enterprise systems (e.g., SAP, Salesforce, Snowflake etc), with CI/CD, automated testing, rollback, and human-in-the-loop controls.
• Establish and enforce governance, safety, and compliance controls—including prompt injection/ jailbreak defenses, policy guardrails, data classification/residency, and PHI/PII handling—in partnership with Security, Legal, and Risk.

Implement evaluation, observability and operations at scale: task-based evals, telemetry and tracing, incident response, and FinOps practices to achieve defined SLAs for reliability, latency, and cost.

Skills and Expertise

Client requires (at a minimum) the following qualifications:

• Master’s in computer science, applied mathematics, or engineering field or a science field (completed and verified prior to star)
• Five (5) years of experience in AI engineering, with at least Two (2) years in a Generative AI, AI driven automation or RPA in a private, public, government or military environment.

Additional qualifications for success in this role include:

• Advanced proficiency in Python and modern software engineering practices + agent frameworks such as LangGraph, AWS Strands or MS AutoGen.
• Experience with RAG/memory architecture (chunking, embeddings, vector DBs, enterprise search/knowledge graphs) and secure integration with SAP/Salesforce/Snowflake.
• Strong command of cloud architecture and governance on AWS or Azure encompassing network isolation, identity and secrets management, and data-protection controls; practical experience implementing AI safety and compliance (prompt-injection and jailbreak mitigation, PHI/PII handling, GDPR/SOC 2).
• Hands-on experience with cloud agent platforms (e.g., AWS Bedrock AgentCore, Azure AI Agent Service/AI foundry) and routing across multiple model providers.
• Familiarity with agent evaluation and risk controls, including offline/online task-based evaluations (e.g., Ragas, DeepEval), guardrail/policy engines, prompt-injection/jailbreak mitigation, and PHI/PII protection.
• Working knowledge of enterprise-scale integration and operations (Mulesoft, SAP BTP) workflow orchestration (Power Platform, Airflow), event streaming (Kafka/Kinesis), and FinOps techniques (caching, batching, rate limiting).