below marketmost similar roles pay hereabove market
This role pays more than
51%
of similar roles. Most pay
$195,750–$277,512
— the blue band above.
At the midpoint, this role pays about
$235k
versus about
$237k
for comparable roles.
Based on 240 similar postings.
Employer
About Citi
Citi is one of the world’s most trusted financial institutions, proudly serving millions of customers across the United States.
Citi currently has
268 open roles
on FindRole.
Listed pay typically runs
$125,760–$188,640
across 251 roles with salary data.
The Principal AI Architect - Director joins the Applied AI and Agents Factory to serve as the chief technical authority for autonomous systems and multi-agent frameworks. You will define enterprise architectural visions, author reference blueprints for hierarchical sub-agent and Human-in-the-Loop workflows, and chair the Agent Architecture Review Board. Responsibilities include translating field friction into platform features, establishing standards for Model Context Protocol server integration, and enforcing zero-trust boundaries. You will utilize Python, Golang, OpenShift, Kubernetes, and tools like LangGraph, AutoGen, CrewAI, and Semantic Kernel. The role addresses the technical challenge of building production-ready, non-deterministic AI systems that reason and execute multi-step workflows while ensuring compliance with financial services Model Risk Management standards and enterprise telemetry requirements using OpenTelemetry and Splunk.
Serve as the chief technical authority for autonomous systems and multi-agent frameworks across the global technology footprint.
Author and maintain enterprise reference architectures and blueprints for single-agent, hierarchical, and Human-in-the-Loop workflows.
Act as the primary technical bridge to translate field friction into core platform features for internal systems.
Chair the Agent Architecture Review Board to conduct mandatory technical and security reviews for high-risk AI agents.
Define enterprise standards for Model Context Protocol integration, zero-trust boundary enforcement, and identity token delegation.
Establish horizontal governance for code quality, testability, and automated evaluation standards across all engineering pods.
Advise senior leadership on emerging AI paradigms, non-deterministic system validation, and foundation model capabilities.
What we're looking for
10+ years of progressive software architecture and engineering experience in enterprise, distributed systems, or financial technology environments.
3+ years of hands-on experience architecting and deploying production LLM-powered applications, multi-agent systems, and autonomous agentic workflows.
Mastery of Python and/or Golang, OpenShift/Kubernetes, distributed microservices, OAuth2/JWT token delegation, API gateway management, and enterprise telemetry.
Deep understanding of financial services compliance, Model Risk Management (MRM) standards, and deterministic validation methodologies for non-deterministic AI outputs.
Demonstrated leadership and track record of chairing technical governance bodies and influencing enterprise-level architectural direction.
Consistently demonstrates clear, concise, and persuasive executive-level written and verbal communication.
Bachelor’s/University degree or equivalent experience.
Master’s degree in Computer Science, AI/ML, or related technical field (preferred).
AI
LLM
Agentic Workflows
Vector Search
AI Orchestration
Distributed Systems
APIs
Cloud-Native
Data Platforms
AI Governance
Observability
Security
Privacy
Compliance
AI
Agentic Systems
Model Serving
Multi-model Orchestration
AWS
GCP
Azure
API
MCP
infrastructure-as-code
FinOps
Responsible AI
Model Evaluation
Guardrails
Artificial Intelligence
Machine Learning
API Design
Web Frameworks
Software Architecture
System Design
Identity and Access Management
Software Development Lifecycle
Integration Patterns