Senior Director, Agentic Engineering

Truist Bank•Charlotte, NC

12d

About The Position

The Senior Director of Agentic Engineering leads the engineering, evolution, and operation of enterprise foundation services that enable teams to securely build, deploy, govern, and operate agentic AI solutions at scale. The role establishes engineering direction and develops reusable agentic capabilities, enterprise context services, patterns, controls, integrations, and automation that support adoption while meeting enterprise expectations for security, resiliency, portability, observability, traceability, and operational readiness. This position combines first-hand agentic AI and AWS engineering expertise with senior technology leadership. The Senior Director provides technical direction while building teams, setting standards, managing complex dependencies, and developing durable enterprise foundation services. The role takes responsibility for existing agentic engineering capabilities and advances them through their full lifecycle, while defining how agents can operate as accountable enterprise workforce contributors with clear ownership, autonomy, governance, and lifecycle management.

Requirements

Bachelor’s degree or higher in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent education, training, and work-related experience.
At least 12 years of progressive technology and engineering experience, including significant experience leading complex engineering organizations and enterprise technology initiatives.
Demonstrated experience building, leading, and developing high-performing engineering teams responsible for complex, production-scale platforms or foundation services.
Deep, first-hand engineering experience with generative AI and agentic AI systems, including the technical ability to engage in architecture, design, implementation, troubleshooting, and engineering trade-off discussions.
First-hand implementation experience with Amazon Bedrock and Amazon Bedrock AgentCore, including building or integrating production-oriented agentic capabilities on AWS.
First-hand experience applying Amazon Bedrock, Amazon Bedrock AgentCore, Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Amazon Bedrock Data Automation, Amazon Neptune, AWS Glue, Amazon CloudWatch, AWS CloudTrail, and AWS IAM within secure enterprise architectures.
Understanding of agentic architecture and engineering patterns, including orchestration, tool integration, grounding and knowledge retrieval, context and memory, authorization, human oversight, and safe-operation controls.
Experience designing agentic systems with explicit approaches to agent identity, ownership, authorization, autonomy, human oversight, auditability, and lifecycle management.
Experience designing AI platforms and applications for model and provider portability, systematically evaluating model quality, safety, performance, cost, and fitness for purpose, and using evaluation criteria to govern production promotion.
Experience engineering enterprise context and knowledge capabilities, including retrieval-augmented generation, knowledge bases, graph and ontology approaches, enterprise data integration, semantic context, and agent memory.
Strong software and platform engineering experience establishing reusable services, APIs, infrastructure-as-code, CI/CD practices, engineering standards, observability, and operational controls.
Experience designing and operating secure cloud architectures, including identity and access management, workload isolation, network controls, policy enforcement, logging, monitoring, and auditability.
Ability to solve difficult, multi-team engineering problems involving dependencies across applications, cloud infrastructure, security, data, architecture, and enterprise governance.
Strong executive and technical communication skills, with the ability to move between detailed engineering discussions and senior-level business, risk, and technology conversations.
Ability to lead technology transformation in a complex enterprise environment while balancing innovation, delivery velocity, resiliency, security, risk, and governance.

Nice To Haves

Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related technical discipline.
Experience establishing or leading enterprise AI, generative AI, agentic AI, cloud platform, or developer platform engineering organizations.
Experience building shared foundation services for multiple application or product teams, particularly where standardization, reuse, developer experience, and governed self-service are key objectives.
Experience engineering AI capabilities in a regulated financial-services or similarly regulated environment.
Experience with graph-based knowledge representation, ontologies, retrieval-augmented generation, enterprise knowledge integration, semantic architectures, and advanced grounding patterns.
Experience establishing technical approaches to AI and agent evaluation, responsible AI controls, traceability, human oversight, and production monitoring.
Experience evaluating and engineering emerging agentic patterns, including long-running agents, multi-agent orchestration, and computer-use capabilities.
AWS technical certifications or comparable demonstrated expertise in AWS architecture and engineering.

Responsibilities

Lead Agentic Engineering as an enterprise engineering capability, providing technical and organizational leadership for teams responsible for foundation services, frameworks, reusable components, engineering patterns, and platform integrations.
Own the engineering lifecycle of enterprise agentic foundation services, from architecture and implementation through deployment, adoption, operation, modernization, optimization, and ongoing evolution.
Lead the engineering and evolution of AWS-based agentic capabilities, particularly Amazon Bedrock and Amazon Bedrock AgentCore, including governed access to models, agents, tools, knowledge, data, and enterprise systems.
Define the operating model for agents as accountable enterprise workforce contributors, including ownership, accountability, autonomy tiers, permitted actions, oversight, controls, and lifecycle management.
Establish reusable engineering patterns that enable teams to build agentic solutions safely and consistently, including approaches to onboarding, deployment, integration, operation, and lifecycle management.
Drive the shift from human-executed processes toward self-service, automated, and agent-executed capabilities, with patterns and controls for safe and increasingly autonomous activity.
Own the enterprise context layer as a product, providing governed capabilities for agents to discover, access, interpret, and use enterprise knowledge, data, relationships, semantics, and context.
Establish reusable approaches for knowledge bases, retrieval, graph and ontology capabilities, memory, data integration, and contextual grounding.
Drive engineering of agentic control-plane capabilities, including gateways, authorization and policy enforcement, identity and access controls, model access, guardrails, agent and tool registration, deployment automation, private connectivity, and operational controls.
Establish provider-portable agentic engineering patterns and evaluation-gated promotion practices for model and provider changes, using defined quality, risk, performance, cost, and operational criteria.
Maintain an agentic engineering roadmap and develop enterprise patterns for emerging capabilities such as long-running agents, multi-agent systems, advanced orchestration, and computer-use patterns.
Integrate security, risk, privacy, and governance into the platform in partnership with enterprise architecture, cybersecurity, risk, data, infrastructure, and other control partners.
Advance observability, traceability, and operational engineering, including logging, monitoring, telemetry, auditability, and operational controls for production workloads.
Build automation and infrastructure-as-code patterns for repeatable deployment and onboarding, advancing toward scalable self-service and agent-executed provisioning, configuration, testing, deployment, and operations where appropriate.
Establish engineering and evaluation standards for production-quality agentic systems, including software engineering, agent and model evaluation, release management, resiliency, performance, security, operational readiness, and lifecycle management.
Lead complex engineering initiatives across organizational boundaries, managing technical dependencies, sequencing, critical-path work, engineering decisions, and delivery risks.
Partner with product, strategy, architecture, security, data, infrastructure, application, and business teams to translate agentic AI needs into prioritized engineering capabilities and reusable enterprise services.
Provide authoritative technical leadership by reviewing designs, challenging assumptions, evaluating emerging capabilities, resolving difficult technical problems, and making informed build, integrate, or adopt decisions.
Develop and execute short- to mid-term engineering and operational plans aligned with broader AI, data, cloud, and enterprise technology strategies.
Build and develop a high-performing engineering organization through workforce planning, talent acquisition, technical capability development, coaching, performance management, succession planning, and development of future engineering leaders.
Manage third-party and strategic technology relationships as needed, ensuring external capabilities and contributions meet enterprise architecture, engineering, security, operational, and quality expectations.
Steward the organization's financial and operational resources, including workforce, technology consumption, vendor expenditures, and associated costs.
Drive continuous modernization and simplification to improve the foundation, reduce friction, increase reuse and portability, strengthen controls, and improve engineering and operational efficiency.

Benefits

Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
Accidental death and dismemberment coverage
Tax-preferred savings accounts
401(k) plan
At least 10 days of vacation during the first year, prorated based on hire date and full-time or part-time status
10 sick days, prorated
Paid holidays
Depending on position and division, eligibility for a defined benefit pension plan, restricted stock units, and/or a deferred compensation plan