Principal AI Architect
Indexed description
Responsibilities
Enterprise AI & GenAI Architecture
- Define and own enterprise AI and GenAI reference architectures, including LLM platforms, RAG patterns, agentic systems, and multimodal solutions.
- Establish standardized architectural patterns for model serving, prompt management, orchestration, tool use, and agent frameworks.
- Lead architecture decisions for buy vs. build, model selection, hosting strategies, and vendor integrations.
- Ensure AI architectures align with enterprise standards, cloud strategy, security, and governance.
- Prototype and operationalize advanced AI solutions, including GenAI and LLM-based systems. Architect end-to-end MLOps capabilities, including model lifecycle management, CI/CD for ML, feature stores, model monitoring, and drift detection.
- Define enterprise patterns for training, fine-tuning, deployment, and observability of ML and GenAI workloads.
- Guide teams on productionizing PoCs into scalable, resilient, and supportable AI systems.
- Partner with platform teams to evolve a shared enterprise AI platform.
- Design AI and GenAI solutions using AWS-native services, including (but not limited to):
- Amazon Bedrock, SageMaker, Lambda, ECS/EKS
- S3, DynamoDB, Aurora, OpenSearch
- IAM, KMS, VPC, CloudWatch
- Define cost, performance, and scalability guardrails for AI workloads on AWS.
- Ensure architectures follow Well-Architected Framework principles.
- Partner with security, legal, and compliance teams to define AI governance, guardrails, and controls.
- Embed responsible AI principles, data privacy, and explainability into enterprise designs.
- Establish standards for model access, auditability, and risk management.
- Act as a principal-level advisor to senior technology and business leaders. Champion hands-on experimentation and rapid solution delivery while maintaining technical excellence.
- Mentor architects and senior engineers on AI architecture and MLOps best practices.
- Drive alignment across teams by publishing reference architecture, design standards, and decision frameworks.
- Represent the organization in architecture forums, reviews, and strategic initiatives.
Preferred Qualifications
- 10+ years of experience in enterprise architecture, data platforms, or distributed systems.
- Deep expertise in AI/ML architecture, including GenAI and LLM-based systems.
- Strong experience designing MLOps platforms and enterprise AI foundations.
- Proven experience architecting solutions on AWS.
- Experience with Snowflake Cortex AI, Snowflake Native AI capabilities
- Strong understanding of cloud security, networking, and governance.
- Proficiency in Python, SQL, and modern data frameworks (e.g., Databricks, Airflow, Snowflake, Vertex AI).
- Relevant AWS certifications in cloud architecture, AI/ML, generative AI, or related domains.
- Experience with agentic AI design patterns, including tool-use orchestration, autonomous workflow agents, or AI copilots.
- Proficiency in API design, microservices, and containerization (Docker, Kubernetes).
- Demonstrated ability to rapidly prototype new AI concepts and transition successful PoCs into production-grade systems.
Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.
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