AI Leader

Role: AI Leader – Agentic Systems & Enterprise AI Enablement Location: Carmel, IN (Relocation required; assistance available)
Employment Type: Full-time Employee

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. 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.
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.
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.
Act as a player/coach with the ability to mentor engineers, data scientists, solution architects, and functional teams.
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.
Serve as the strategic AI advisor to senior executives and technology leaders, helping them define roadmaps, governance, and investment strategies.
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.
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.
~ 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.