PerficientRemote
Hands-on Lead AI Workflow and Automation Engineer
United States of America
Full Time
2 hours ago
$73,000 - $171,000 USD
No H1B
Key skills
API-driven workflowsBusiness Process Management (BPM)User Interface (UI) integrationAutomation frameworksWorkflow orchestrationLow-code/no-code platforms.NETAngularAWSAI architecturesPrompt engineeringLarge Language Model (LLM) integrationsAI discoverability designSoftware designData structuresAlgorithmsAgile methodologiesTechnical documentation authoringAILLMAgile
About this role
Perficient is a global AI and technology consulting firm, and they are seeking a Hands-on Lead AI Workflow and Automation Engineer to join their hybrid team. In this role, you will lead the design, development, and implementation of scalable AI-driven workflows while ensuring that all future business capabilities are built with an AI-first mindset.
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
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
- 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
- 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
- Client facing or consulting experience highly preferred