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Principal Agentic AI Architect
Job Location:
Job Location:
Charlotte, NC - USA
Hourly Salary:
USD 65 - 75
Hourly Salary:
Posted:
28 October 2026 (11 hours ago)
Posted:
Application Deadline:
25 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Title: Principal Agentic AI Architect
Location: Charlotte NC
Work Model: Day 1 Onsite
Rate: $65$75/hour
Job Summary
Key Responsibilities
1. Technical Leadership & Architecture
Define and drive long-term technology strategy for Financial Crime modernization initiatives.
Lead the architecture and implementation of AI-powered investigation platforms decisioning engines and agentic workflows.
Establish engineering standards design patterns and reference architectures across Financial Crime platforms.
Serve as the senior technical authority for architecture security scalability resiliency and performance decisions.
Lead technical design reviews and influence enterprise architecture direction.
2. AI & Agentic Engineering
Design and implement Generative AI and Agentic AI solutions for:
Investigator copilots
Alert triage and disposition
Risk assessment
Entity resolution
Suspicious Activity Report (SAR) narrative generation
Customer screening
Knowledge retrieval and decisioning
Evaluate and implement modern AI technologies including LLM orchestration frameworks agent frameworks vector databases Retrieval-Augmented Generation (RAG) model routing guardrails and AI observability.
Partner with Data Science teams to operationalize AI/ML models and deploy scalable production-ready AI platforms.
Ensure AI solutions address security reliability explainability governance and responsible AI requirements.
3. Engineering Excellence
Write and review high-quality production code when required.
Lead proof-of-concepts (POCs) rapid prototyping and technical spikes.
Mentor senior engineers and establish software engineering best practices.
Drive automation CI/CD DevSecOps testing and operational excellence.
Resolve complex technical challenges across multiple platforms and engineering teams.
4. Platform Modernization
Lead migration from legacy Financial Crime applications to cloud-native architectures.
Architect scalable microservices event-driven systems and API-first platforms.
Design enterprise capabilities for:
Real-time risk assessment
Customer screening
Case management
Regulatory reporting
AI orchestration
Data ingestion and processing
Drive platform modernization using cloud technologies and enterprise architecture standards.
5. Stakeholder Collaboration
Collaborate with Product Compliance Risk Operations Data Science and Engineering leadership.
Translate business requirements into scalable secure and maintainable technical solutions.
Present architecture strategies technical recommendations and modernization roadmaps to senior technology executives.
Build consensus across business and technology teams to deliver strategic initiatives.
Required Qualifications
7 years of engineering experience or equivalent demonstrated through work experience training military experience education or a combination thereof.
7 years of experience architecting designing and leading the delivery of large-scale technology solutions.
4 years of experience presenting technology strategy and concepts to C-level executives and large audiences.
5 years of experience delivering cloud-ready and cloud-native solutions.
Desired Qualifications
2 years of experience developing or deploying AI-powered tools chatbots LLM-based automation or agentic workflows.
Understanding of AI risks observability requirements and stakeholder communication.
4 years of experience in the Financial Services industry.
Excellent verbal written and interpersonal communication skills.
Strong analytical problem-solving and decision-making abilities.
Ability to prioritize competing demands meet deadlines achieve goals and perform effectively under pressure.
Core Technical Competencies
Generative AI (GenAI) and Agentic AI
Large Language Models (LLMs) and LLM orchestration
Retrieval-Augmented Generation (RAG) and vector databases
AI agents guardrails model routing and observability
Cloud-native architecture and distributed systems
Microservices event-driven architecture and API design
AI/ML model integration and production deployment
CI/CD DevSecOps automation and software engineering best practices
Financial Crime Anti-Money Laundering (AML) customer screening risk assessment and regulatory reporting
Location: Charlotte NC
Work Model: Day 1 Onsite
Rate: $65$75/hour
Job Summary
- We are seeking an experienced Principal Agentic AI Architect to lead the architecture design and implementation of AI-powered solutions for Financial Crime modernization initiatives.
- The ideal candidate will have strong expertise in enterprise architecture Generative AI (GenAI) Agentic AI cloud-native platforms and large-scale distributed systems.
- The candidate will drive technology strategy architect intelligent investigation and decisioning platforms and lead the modernization of legacy financial crime applications.
- This role requires close collaboration with Product Compliance Risk Operations Data Science and Engineering teams to deliver secure scalable resilient and production-ready AI solutions.
Key Responsibilities
1. Technical Leadership & Architecture
Define and drive long-term technology strategy for Financial Crime modernization initiatives.
Lead the architecture and implementation of AI-powered investigation platforms decisioning engines and agentic workflows.
Establish engineering standards design patterns and reference architectures across Financial Crime platforms.
Serve as the senior technical authority for architecture security scalability resiliency and performance decisions.
Lead technical design reviews and influence enterprise architecture direction.
2. AI & Agentic Engineering
Design and implement Generative AI and Agentic AI solutions for:
Investigator copilots
Alert triage and disposition
Risk assessment
Entity resolution
Suspicious Activity Report (SAR) narrative generation
Customer screening
Knowledge retrieval and decisioning
Evaluate and implement modern AI technologies including LLM orchestration frameworks agent frameworks vector databases Retrieval-Augmented Generation (RAG) model routing guardrails and AI observability.
Partner with Data Science teams to operationalize AI/ML models and deploy scalable production-ready AI platforms.
Ensure AI solutions address security reliability explainability governance and responsible AI requirements.
3. Engineering Excellence
Write and review high-quality production code when required.
Lead proof-of-concepts (POCs) rapid prototyping and technical spikes.
Mentor senior engineers and establish software engineering best practices.
Drive automation CI/CD DevSecOps testing and operational excellence.
Resolve complex technical challenges across multiple platforms and engineering teams.
4. Platform Modernization
Lead migration from legacy Financial Crime applications to cloud-native architectures.
Architect scalable microservices event-driven systems and API-first platforms.
Design enterprise capabilities for:
Real-time risk assessment
Customer screening
Case management
Regulatory reporting
AI orchestration
Data ingestion and processing
Drive platform modernization using cloud technologies and enterprise architecture standards.
5. Stakeholder Collaboration
Collaborate with Product Compliance Risk Operations Data Science and Engineering leadership.
Translate business requirements into scalable secure and maintainable technical solutions.
Present architecture strategies technical recommendations and modernization roadmaps to senior technology executives.
Build consensus across business and technology teams to deliver strategic initiatives.
Required Qualifications
7 years of engineering experience or equivalent demonstrated through work experience training military experience education or a combination thereof.
7 years of experience architecting designing and leading the delivery of large-scale technology solutions.
4 years of experience presenting technology strategy and concepts to C-level executives and large audiences.
5 years of experience delivering cloud-ready and cloud-native solutions.
Desired Qualifications
2 years of experience developing or deploying AI-powered tools chatbots LLM-based automation or agentic workflows.
Understanding of AI risks observability requirements and stakeholder communication.
4 years of experience in the Financial Services industry.
Excellent verbal written and interpersonal communication skills.
Strong analytical problem-solving and decision-making abilities.
Ability to prioritize competing demands meet deadlines achieve goals and perform effectively under pressure.
Core Technical Competencies
Generative AI (GenAI) and Agentic AI
Large Language Models (LLMs) and LLM orchestration
Retrieval-Augmented Generation (RAG) and vector databases
AI agents guardrails model routing and observability
Cloud-native architecture and distributed systems
Microservices event-driven architecture and API design
AI/ML model integration and production deployment
CI/CD DevSecOps automation and software engineering best practices
Financial Crime Anti-Money Laundering (AML) customer screening risk assessment and regulatory reporting
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Required Experience:
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