Senior AI Agentic Engineer

Truist • Charlotte, NC

22h • Onsite

About The Position

The Senior AI Agentic Engineer is a senior production builder responsible for designing, implementing, testing, and operating enterprise-grade agentic systems that solve real business problems at scale. This role sits at the center of the Forge delivery model, translating approved architecture patterns into production workflows that combine prompts, tools, APIs, memory, retrieval, orchestration logic, and human oversight into working enterprise capabilities. This is a hands-on senior engineering role focused on agent workflows, multi-step reasoning, prompt architecture, tool integration, memory/context management, retrieval-augmented generation (RAG), evaluation, observability, and governed deployment. The engineer works across platforms and frameworks used to deliver production AI capabilities, including Microsoft and Azure-based agent platforms, enterprise workflow tooling, and other approved agentic engineering stacks where needed. Daily work includes building agent flows, implementing orchestration logic, integrating APIs and enterprise systems, tuning prompts and execution patterns, validating output quality, hardening reliability, instrumenting observability, and supporting secure deployment through enterprise release controls. The role is expected to operate with senior-level ownership, production judgment, and deep technical accountability while still moving at startup speed inside enterprise governance. For this opportunity, Truist will not sponsor an applicant for work visa status or employment authorization, nor will we offer any immigration-related support for this position (including, but not limited to H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN-1 or TN-2, E-3, O-1, or future sponsorship for U.S. lawful permanent residence status.)

Requirements

• Bachelor’s degree and eight to twelve years of experience as a developer or equivalent education and related training or experience
• Deep specialized and/or broad functional knowledge
• Sound understanding of business and organizational strategies and processes
• Ability to interpret internal and external business challenges and recommend best practices
• Ability to lead complex projects
• Sophisticated analytical skills and the ability to solve complex technical and business problems
• Ability to influence others at senior levels to adopt a new perspective
• 5+ years of software engineering experience, including strong hands-on experience building and supporting production systems in enterprise environments.
• Strong programming ability in Python and working knowledge of TypeScript, JavaScript, or another modern language commonly used in enterprise engineering stacks.
• Demonstrated experience building AI-enabled applications, prompt-driven workflows, orchestration logic, or agentic systems that move beyond simple chat responses.
• Experience integrating APIs, enterprise systems, workflow services, tools, and governed data sources into applications or automations with production-grade reliability.
• Strong understanding of prompt design, tool-calling, workflow branching, context handling, and engineering patterns required to make AI systems dependable in production.
• Experience with automated testing, CI/CD, code review, observability, and release controls in modern engineering organizations.
• Ability to work across architecture, implementation, reliability, security, and operational concerns instead of only isolated coding tasks.
• Strong written and verbal communication skills and the ability to operate effectively in cross-functional enterprise delivery teams.

Nice To Haves

• Experience with enterprise agent platforms, workflow automation tools, or AI delivery stacks used for production business solutions.
• Experience with Microsoft, Azure, Copilot / Copilot Studio, Power Platform, or enterprise AI productivity and orchestration ecosystems.
• Experience with RAG, vector stores, retrieval pipelines, enterprise knowledge grounding, memory-aware agent behavior, or multi-agent collaboration patterns.
• Experience validating or tuning AI outputs for accuracy, consistency, policy adherence, and business usefulness in production-style scenarios.
• Experience in financial services, cybersecurity, risk-managed enterprise environments, or other heavily governed production settings.
• Experience mentoring other engineers, reviewing architecture or code quality, and functioning as a senior technical contributor with broad delivery impact.
• Experience working with observability, telemetry, production incident handling, and operational runbooks for complex AI-enabled systems.

Responsibilities

• Design, build, and deploy production-ready AI agents and agentic workflows that combine prompts, tools, APIs, memory, retrieval, and business logic into useful enterprise capabilities.
• Implement single-agent and multi-agent workflows using approved Forge patterns, including tool orchestration, supervisor-worker patterns, human-in-the-loop controls, session-aware execution, and safe fallback behaviors.
• Translate architecture and product intent into robust implementations that are observable, testable, secure, and maintainable in enterprise production environments.
• Build and maintain integrations to enterprise systems, APIs, workflow services, and governed data sources that enable agents to act safely and effectively within approved boundaries.
• Design and maintain prompt architectures, tool schemas, retrieval logic, memory behavior, and structured execution controls that improve agent accuracy, reliability, and explainability.
• Contribute to RAG, grounding, and knowledge-retrieval patterns using search, vector stores, document pipelines, and governed enterprise data services.
• Implement runtime controls for resilience and safety, including error handling, retries, tool constraints, structured outputs, human escalation, and observable execution behavior.
• Support evaluation and regression validation for agentic solutions, including prompt changes, model changes, workflow changes, and quality benchmarks tied to business outcomes.
• Use approved engineering acceleration tools to speed code generation, testing, refactoring, and documentation while remaining accountable for production quality and correctness.
• Write and maintain automated tests, integration validations, deployment-readiness checks, and runbooks for agent-enabled solutions and their supporting services.
• Partner with architecture, security, QA, product, data, platform, and enablement teams to move AI capabilities from design into reliable production delivery.
• Contribute reusable engineering patterns, reference implementations, and technical guidance that raise delivery quality and speed across the broader Forge engineering 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: Mid Level