Qode
AI Lead - Agentic AI Consultant
TLDR
Lead the design and delivery of enterprise-grade Agentic AI solutions for Fortune 500 clients, focusing on technical innovation and consulting value across multiple industries.
AI LEAD — AGENTIC AI CONSULTANT
Charlotte, NC · New York, NY · Hybrid
Full-Time · Senior / Principal Level · Technology Consulting
Function
AI & Digital Transformation — Agentic Systems Practice
Level
Principal Consultant
Locations
Charlotte, NC | New York, NY | Hybrid
About the Role
We are looking for a visionary AI Lead to spearhead the design, development, and delivery of enterprise-grade Agentic AI solutions. In this role you will combine deep technical expertise in large language models (LLMs), autonomous agent orchestration, and multi-agent frameworks with a sharp consulting mindset to drive measurable business value for Fortune 500 clients across financial services, healthcare, and retail verticals.
As the practice lead you will own the end-to-end agentic AI delivery lifecycle — from opportunity identification and solution architecture through implementation, change management, and post-deployment optimization — while simultaneously growing a high-performing team and shaping internal AI methodology.
LLM / GenAI
Multi-Agent Systems
RAG Pipelines
AI Strategy
Enterprise Architecture
Key Responsibilities
Client Delivery & Solutioning
• Architect and lead delivery of Agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration layers on Azure / AWS / GCP.
• Design multi-agent pipelines incorporating reasoning, planning, tool-use, memory, and feedback loops tailored to enterprise workflows.
• Partner with C-suite and senior stakeholders to translate ambiguous business challenges into well-scoped AI roadmaps and delivery plans.
• Conduct AI readiness assessments, data audits, and opportunity prioritization workshops for prospective clients.
Technical Leadership
• Define reference architectures for RAG, tool-augmented agents, AI gateways, and human-in-the-loop workflows.
• Drive responsible AI governance — including bias audits, hallucination mitigation, prompt-injection hardening, and model risk frameworks.
• Establish engineering best practices: CI/CD for ML, LLMOps, evaluation harnesses, and performance benchmarking.
• Stay at the cutting edge — evaluate emerging models (GPT-o3, Claude 3.x, Gemini Ultra, open-source LLMs) and tooling for fit-for-purpose applicability.
Practice & Business Development
• Originate and expand client relationships; contribute to proposals, RFP responses, and Statements of Work.
• Build and scale the agentic AI practice — create reusable accelerators, IP assets, and delivery playbooks.
• Mentor and develop a team of AI engineers, ML scientists, and business analysts; conduct performance reviews and career development planning.
• Represent the firm at conferences, publish thought-leadership content, and contribute to the external AI community.
Required Qualifications
• 8+ years of overall technology experience with at least 3 years focused on AI / ML systems in a consulting, product, or enterprise engineering capacity.
• Proven hands-on experience designing and deploying LLM-based applications and autonomous agent systems in production environments.
• Proficiency in Python and relevant AI/ML libraries (LangChain, LlamaIndex, Hugging Face Transformers, PyTorch / TensorFlow).
• Deep familiarity with vector databases (Pinecone, Weaviate, pgvector), semantic search, and knowledge graph integration.
• Experience with cloud AI platforms: Azure OpenAI Service, AWS Bedrock, or Google Vertex AI.
• Strong understanding of prompt engineering, fine-tuning (LoRA, QLoRA, RLHF), and model evaluation methodologies.
• Exceptional executive communication skills — ability to present complex AI concepts to non-technical senior leadership.
• Bachelor's or Master's degree in Computer Science, Data Science, AI, Engineering, or a closely related field.
Preferred Qualifications
• Industry certifications: AWS Certified ML Specialty, Google Professional ML Engineer, Azure AI Engineer Associate.
• Experience with agentic frameworks at scale: LangGraph, Microsoft Semantic Kernel, Autogen, or similar.
• Background in financial services, healthcare, or retail — understanding of sector-specific regulatory and compliance constraints.
• Published research, patents, open-source contributions, or conference speaking on AI/ML topics.
• Prior consulting experience at a Big-4, boutique AI firm, or hyperscaler professional services division.
• Familiarity with enterprise integration patterns, API management, and MLOps tooling (MLflow, Weights & Biases, SageMaker Pipelines).
Qode is a technology-driven platform that transforms how recruiters and candidates connect by leveraging data and automation. Our solutions streamline the hiring process through machine learning, creating private talent pools and automating workflows, ultimately enhancing the quality of candidate evaluation and decision-making. With our no-code tools, we empower organizations to develop tailored recruitment strategies without needing extensive technical skills.
- Industry
- Internet Software & Services
Consultant