Senior Principal Enterprise Architect - Principal AI/ML Engineer

Truist • Raleigh, NC

2d

About The Position

The position is described below. If you want to apply, click the Apply Now button at the top or bottom of this page. After you click Apply Now and complete your application, you'll be invited to create a profile, which will let you see your application status and any communications. If you already have a profile with us, you can log in to check status. Need Help? If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response). Please review the following job description: Teammate reports to the division head of enterprise architecture for EA division such a commercial banking and is accountable for a squad (squad (e.g. Lending, Insurance, Mortgage, Security, Platform, Cloud, Payments, Online Banking, etc.). He/She will focus on business capabilities, application/platforms/system architecture elements enterprise wide. Leads in the development of enterprise architecture standards, enforcement and compliance. Applies advanced knowledge of the business and IT architecture principles to identify and evaluate alternatives solutions. Leads the selection of methodologies, tools, and components of total IT solutions. Provides guidance and support for SA's to implement complex architectural strategy and direction of multiple and diverse application / data/network disciplines on a variety of multi-platform systems. Develops business-system architecture plans and reviews cost and feasibility of system requests while ensuring the plan supports the strategic needs of the company. Interprets internal/ external business challenges and recommends best practices. Uses sophisticated analytical thought to exercise judgment and identify innovative solutions. Mentors less experienced teammates to build technical expertise. As a Principal AI/ML Engineer, you will serve as a hands‑on technical authority driving the architecture, design, and delivery of next‑generation AI systems across AWS and Azure. You will shape multi‑agent architectures, guide ML platform strategy, and partner with senior engineering, product, and enterprise leaders to define how AI is built and deployed at scale. This role balances deep technical execution with cross‑org influence, thought leadership, and coaching of engineering teams. ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time. Top-down enterprise design with focus on business model, digital transformation and innovation i.e. collaborate with business owners, technology leaders and risk partners to draft the tech strategy, reflecting the corporate objectives/strategy IT Landscape design in the context of business capabilities of the organization supporting enterprise objective, cost and risk reduction Lead cross cutting enterprise solution design that span across multiple CIOs and domains Set strategic direction for the assigned major business division in alignment with the Business Strategy and Technology standards and provide thought leadership in the development of an enterprise strategic IT plan. Maintain a high level of awareness and understanding of existing and emerging technologies, as well as industry and bank issues, to effectively match them. End to end accountability to review and approve design solutions that best meet the business needs of the enterprise, with a primary focus on innovation. Lead or "jump start" initiatives deemed critical to IT Services and Truist's success Provide thought leadership in new technology innovation, incubation, introduction and implementation critical to Truist's technology and business strategy roadmaps and ongoing success Architect and lead the development of complex, distributed AI/ML systems leveraging AWS AgentCore for agentic workflows and Azure Service Fabric for resilient microservice‑based execution models. Own the end‑to‑end design of enterprise‑grade LLM agents, multi-agent systems, RAG frameworks, and tool‑augmented pipelines that integrate with heterogeneous data and application ecosystems. Define the technical vision for scalable AI infrastructures across AWS and Azure, including data platforms, orchestration frameworks, container environments, and secure production deployment patterns. Direct and oversee large‑scale model lifecycle initiatives: feature engineering, training, evaluation, deployment, observability, drift detection, and continuous improvement. Create standards and reusable architecture patterns for AgentCore‑based agent workflows, vector stores, prompt‑chain orchestration, and secure model interactions. Provide senior‑level guidance on model optimization, fine‑tuning, distributed training, inference acceleration, and cost governance across multi‑cloud environments. Lead technical due diligence, platform evaluations, and strategic recommendations for AI modernization and enterprise adoption. Establish CI/CD and MLOps best practices using AWS CodePipeline, SageMaker Pipelines, Azure ML Ops, and cloud‑native container platforms. Drive innovation through experimentation, POCs, and emerging model integration, acting as a thought leader for advanced AI engineering across the organization. Note: The difference between Sr. Principal Enterprise Architect and Sr. Enterprise Architect is scope, years of experience, and complexity of the business line and related technologies.

Requirements

• Bachelor's degree in Business or IT, or equivalent education and related training
• Recognized professional in their field of expertise. Likely to be published, hold advanced degrees and/or contributed in the advancement of their area(s) of study outside the company and across industry.
• Fifteen years of architecture/design/delivery experience which includes ten years of enterprise architecture experience or fifteen years' solution architecture experience in technology and security, and ten years of banking/financial business domain
• Comprehensive experience with various architectural domains such as application, data, infrastructure, security and integration
• Strong analytical and broad architectural skills
• Strong verbal and written communication skills
• Strong negotiation/facilitation skills
• Significant knowledge of current and emerging architecture principles, methodologies and tools
• Experience as negotiator with vendors for relevant products and services
• Demonstrated competency in strategic thinking with ability to differentiate feasible from academic solutions
• Demonstrated thought-leadership skills with the ability to translate high-level business planning information into application needs/solutions
• Demonstrated proficiency in basic computer applications, such as Microsoft Office software products
• Ability to travel, occasionally overnight

Nice To Haves

• Master's degree in field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
• Prior experience shaping AI platform strategy or serving as a principal or staff‑level engineer in a large enterprise environment.
• Experience with Azure ML, AWS SageMaker, Databricks MLflow, or cross‑cloud distributed training frameworks.
• Exposure to enterprise security, compliance frameworks, and responsible AI practices.
• Industry publications, patents, OSS contributions, or conference presentations in AI/ML or distributed systems.
• Demonstrated expertise in designing and shipping enterprise AI systems using AWS AgentCore and developing distributed solutions with Azure Service Fabric.
• Deep proficiency in Python and modern ML ecosystems (HuggingFace, PyTorch, TensorFlow) and proven experience deploying LLMs and multi-agent architectures.
• Mastery of cloud-native design patterns, microservices, containerization (Docker), orchestration (Kubernetes/EKS/AKS), and event-driven architectures.
• Advanced experience with RAG pipelines, vector databases (FAISS, Pinecone, OpenSearch), and production‑ready retrieval systems.
• Strong MLOps background, including automated training, CI/CD for ML, model observability, and governance controls.
• Ability to influence across organizations, drive consensus on architecture decisions, and lead complex technical programs end‑to‑end.

Responsibilities

• Top-down enterprise design with focus on business model, digital transformation and innovation i.e. collaborate with business owners, technology leaders and risk partners to draft the tech strategy, reflecting the corporate objectives/strategy
• IT Landscape design in the context of business capabilities of the organization supporting enterprise objective, cost and risk reduction
• Lead cross cutting enterprise solution design that span across multiple CIOs and domains
• Set strategic direction for the assigned major business division in alignment with the Business Strategy and Technology standards and provide thought leadership in the development of an enterprise strategic IT plan.
• Maintain a high level of awareness and understanding of existing and emerging technologies, as well as industry and bank issues, to effectively match them.
• End to end accountability to review and approve design solutions that best meet the business needs of the enterprise, with a primary focus on innovation.
• Lead or "jump start" initiatives deemed critical to IT Services and Truist's success
• Provide thought leadership in new technology innovation, incubation, introduction and implementation critical to Truist's technology and business strategy roadmaps and ongoing success
• Architect and lead the development of complex, distributed AI/ML systems leveraging AWS AgentCore for agentic workflows and Azure Service Fabric for resilient microservice‑based execution models.
• Own the end‑to‑end design of enterprise‑grade LLM agents, multi-agent systems, RAG frameworks, and tool‑augmented pipelines that integrate with heterogeneous data and application ecosystems.
• Define the technical vision for scalable AI infrastructures across AWS and Azure, including data platforms, orchestration frameworks, container environments, and secure production deployment patterns.
• Direct and oversee large‑scale model lifecycle initiatives: feature engineering, training, evaluation, deployment, observability, drift detection, and continuous improvement.
• Create standards and reusable architecture patterns for AgentCore‑based agent workflows, vector stores, prompt‑chain orchestration, and secure model interactions.
• Provide senior‑level guidance on model optimization, fine‑tuning, distributed training, inference acceleration, and cost governance across multi-cloud environments.
• Lead technical due diligence, platform evaluations, and strategic recommendations for AI modernization and enterprise adoption.
• Establish CI/CD and MLOps best practices using AWS CodePipeline, SageMaker Pipelines, Azure ML Ops, and cloud‑native container platforms.
• Drive innovation through experimentation, POCs, and emerging model integration, acting as a thought leader for advanced AI engineering across the organization.

Benefits

• All regular teammates (not temporary or contingent workers) working 20 hours or more per week are eligible for benefits, though eligibility for specific benefits may be determined by the division of Truist offering the position.
• Truist offers medical, dental, vision, life insurance, disability, accidental death and dismemberment, tax-preferred savings accounts, and a 401k plan to teammates.
• Teammates also receive no less than 10 days of vacation (prorated based on date of hire and by full-time or part-time status) during their first year of employment, along with 10 sick days (also prorated), and paid holidays.
• Depending on the position and division, this job may also be eligible for Truist’s defined benefit pension plan, restricted stock units, and/or a deferred compensation plan.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior