Hands-on Lead AI Workflow and Automation Engineer

Perficient • Charlotte, NC

1d • Hybrid

About The Position

We currently have a career opportunity for an AI Workflow & Automation hands-on Lead Engineer to join our hybrid team located in Charlotte, NC. Job Overview: As a Hands-on Lead AI Workflow and Automation Engineer, you will lead the design, development, and implementation of scalable AI-driven workflows and ensure all future business capabilities are built with an AI-first mindset. As a member working in a team environment you will work with solution architects and developers on interpretation/translation of wireframes and creative designs into functional requirements, and subsequently into technical design.

Requirements

• Strong experience building API-driven, BPM-based, or UI-integrated workflows at enterprise scale.
• Tech Stack : .Net, Angular, AWS
• Expertise in automation frameworks, workflow orchestration, or low/no-code platforms.
• Understanding of modern AI architectures, prompt engineering, and LLM integrations.
• Ability to design systems that are AI-discoverable, modular, and reusable.
• Experience collaborating across engineering, product, and business teams.
• Ability to evangelize and drive cultural change toward AI-first design principles.
• Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support data-informed task execution.
• A solid understanding of AI capabilities and limitations including ethical considerations is expected.
• Client facing or consulting experience highly preferred.
• Skilled problem solvers with the desire and proven ability to create innovative solutions.
• Flexible and adaptable attitude, disciplined to manage multiple responsibilities and adjust to varied environments.
• Future technology leaders- dynamic individuals energized by fast paced personal and professional growth.
• Phenomenal communicators who can explain and present concepts to technical and non-technical audiences alike, including high level decision makers.
• Bachelor’s Degree in MIS, Computer Science, Math, Engineering or comparable major.
• Solid foundation in Computer Science, with strong competencies in data structures, algorithms and software design.
• Knowledge and experience in developing software using agile methodologies.
• Proficient in authoring, editing and presenting technical documents.
• Ability to communicate effectively via multiple channels (verbal, written, etc.) with technical and non-technical staff.

Nice To Haves

• Prior experience implementing enterprise-scale AI assistants or copilots.
• Familiarity with knowledge graphs, metadata frameworks, or semantic models.
• Experience with cloud-native services and modern integration patterns.

Responsibilities

• Build Reusable, Scalable AI Workflows Design and implement reusable AI-enabled workflows across multiple layers, including: APIs Business Process Management (BPM) User Interfaces (UI) Automation pipelines Create a modular, scalable architecture that supports rapid reuse, extension, and integration across business units. Establish standards and patterns for workflow reuse and AI-powered orchestration.
• Drive an “AI-First” Adoption Culture Champion a shift from tool-centric adoption to workflow-centric adoption. Guide teams on how to design business processes with AI as a core component—not an add-on. Partner with product and engineering teams to embed AI thinking into solution design from the outset.
• Build AI-Ready Maintenance and Operational Capabilities Ensure all new business capabilities—including maintenance, support, and operational processes—are designed to be: Consumable by chatbots. Integratable with Copilots or agent-style assistants. Discoverable by AI systems via standardized interfaces. Define patterns and metadata structures so AI can identify, reason about, and execute business functions reliably.
• Enable AI Discoverability Through Business Role Exposure Develop mechanisms to expose business logic, roles, and capabilities in a structured way so AI systems can easily interpret and utilize them. Implement a metadata or knowledge-layer approach enabling AI discoverability and contextual understanding. Create documentation and schema standards to ensure consistency in how capabilities are represented.
• Build Toward Maturity Level 2–4 in AI Adoption Create a roadmap for scaling from Maturity 1 to higher maturity levels (automation → orchestration → autonomous workflows). Establish KPIs and measurement frameworks for workflow adoption and reuse. Provide architectural guidance and governance for AI workflow development across teams.

What This Job Offers

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