AI Leader - Enterprise AI Enablement and Agentic Systems

Role: AI Leader – Agentic Systems & Enterprise AI Enablement

Location: Carmel, IN (Relocation required; assistance available)

Employment Type: Full-time Employee

Overview

Our client is seeking a highly accomplished AI Leader with deep hands-on experience across modern agentic AI technologies, MCP-based architectures, multi-agent orchestration, and enterprise-scale AI enablement. This role is a key member of our client’s extended leadership team and is critical to shaping the firm’s AI strategy, driving adoption, and enabling scalable AI transformation for their global customers.

This is a player-coach position requiring the ability to architect, build, deploy, and operationalize agentic systems—while simultaneously providing thought leadership, coaching teams, and advising executive stakeholders. The ideal candidate combines hands-on technical mastery with strong communication, strategic thinking, and the ability to influence at all organizational levels.

Key Responsibilities

AI Strategy, Architecture & Delivery

• Lead the design, development, deployment, and scaling of agentic AI systems, including MCP-based architectures, multi-agent communication models, and advanced orchestration frameworks.
• Architect and implement agent-to-agent workflows that support autonomy, reasoning, decisioning, planning, and continuous learning across enterprise processes.
• Drive the end-to-end lifecycle of AI solutions: discovery, design, development, testing, deployment, tuning, and operational support.
• Design and enforce standards for secure, reliable, and compliant AI deployments across cloud, on-premise, hybrid, and edge environments.
• Evaluate and integrate emerging AI technologies, LLMs, vector databases, reasoning engines, observability platforms, and integration layers such as Workato, MuleSoft, or other iPaaS platforms.

Agentic Use Case Enablement

• Lead the identification, shaping, prioritization, and execution of high-value agentic AI use cases across business functions such as Finance, Supply Chain, HR, Customer Operations, and IT.
• Translate complex business challenges into agent-based workflows utilizing planning, memory, tooling, and multi-agent collaboration.
• Define standards for AI safety, observability, evaluation, and continuous improvement.
• Partner with product leaders, engineers, and domain SMEs to build robust agentic capabilities that deliver measurable business outcomes.

Leadership & Coaching

• Act as a player/coach with the ability to mentor engineers, data scientists, solution architects, and functional teams.
• Build internal capability uplift programs and develop repeatable delivery frameworks, playbooks, and reusable components.
• Contribute to pre-sales efforts by shaping proposals, presenting architectural POVs, and engaging senior customer stakeholders.
• Serve as an internal champion for AI excellence, fostering a culture of innovation, responsible AI practices, and continuous learning.

Client Engagement & Advisory

• Serve as the strategic AI advisor to senior executives and technology leaders, helping them define roadmaps, governance, and investment strategies.
• Facilitate workshops and strategy sessions to illustrate the potential and responsible use of agentic systems within the enterprise.
• Establish trusted partnerships with customers, ensuring alignment, transparency, and value realization across the AI transformation journey.
• Represent the organization as a thought leader at events, client forums, and technical deep-dive sessions.

Governance, Quality & Scalability

• Define and operationalize best practices for AI governance, MLOps/AIOps, evaluation frameworks, risk mitigation, and responsible AI standards.
• Oversee deployment readiness, performance testing, scalability patterns, and integration across enterprise applications and data landscapes.
• Monitor and remediate solution risks, ensuring stability, security, compliance, and long-term maintainability.
• Drive continuous optimization, scaling roadmaps, and post-production evolution of agentic systems.

Required Skills:

• 10+ years of experience in AI, machine learning, enterprise software engineering, or intelligent automation.
• Proven hands-on experience designing, deploying, and scaling agentic AI systems, including MCP, multi-agent orchestration, and autonomous workflow design.
• Deep technical proficiency with LLMs, vector databases, embeddings, retrieval frameworks, RLHF/RLAIF concepts, tool-use frameworks, and agent reasoning models.
• Expertise in building AI systems with strong reliability, observability, guardrails, and safety controls.
• Demonstrated experience enabling enterprise-grade use cases from concept through scalable production deployment.
• Exceptional communication and storytelling skills with the ability to influence C-suite leaders, functional stakeholders, and technical teams.
• Proven leadership experience as a player-coach, including mentoring and developing teams.

Preferred:

• Experience with advanced OSS agentic frameworks (e.g., LangGraph, CrewAI, AutoGen, or similar) or proprietary enterprise agentic platforms.
• Familiarity with iPaaS solutions (Workato, MuleSoft, Boomi) and cross-domain workflow automation.
• Background supporting AI transformation within consulting, digital services, or SI environments.
• Experience integrating AI into ERP, CRM, ITSM, or supply chain ecosystems (SAP, Salesforce, ServiceNow, etc.).
• Industry certifications in AI, cloud (AWS, Azure, GCP), or responsible AI frameworks.