Automation & Modernization Manager

Job Summary

The AI Modernization Manager is a senior leadership role within the Tech Enablement practice. Working closely with the ITO Director, this role is responsible for defining and executing the organization’s AI modernization strategy across internal operations and client engagements. The manager leads a cross‑functional team of professionals, including AI developers, BI specialists, and Business Analysts and owns nine core practice pillars spanning the full AI lifecycle, from technical architecture and delivery to governance, security, education, and client enablement.

• Own the practice vision, strategy, and roadmap; align with the ITO Director on priorities and escalations.
• Define and govern RAG pipelines, AI agents, agentic workflows, chatbots, LLMs, and AI tooling selection.
• Lead delivery using Agile and AI‑specific PM frameworks; own the practice backlog and sprint execution.
• Establish responsible AI standards, usage policies, and drive adoption across internal teams and clients.
• Oversee BA function; translate business needs from internal teams, clients, and backlog into AI use cases.
• Lead 6–12 members across AI developers, BI specialists, and Business Analysts serving internal and client needs.
• Ensure all AI solutions meet security, data privacy, and compliance standards from design through deployment.
• Own quality assurance and production readiness standards for all AI solutions before go‑live.
• Design and deliver AI training programs for internal teams and client‑facing enablement sessions.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent experience.
• 8+ years in technology roles spanning AI, architecture, data, automation, or analytics platforms.
• Proven experience leading AI modernization or digital transformation initiatives at enterprise scale.
• Hands‑on knowledge of AI/ML concepts: RAG, AI agents, agentic frameworks, chatbots, and LLM integrations.
• Experience with AI cloud platforms such as Azure OpenAI, AWS Bedrock, or equivalent.
• Agile and/or AI‑specific project management experience; ability to run delivery backlogs and sprint cycles.
• Demonstrated leadership of cross‑functional technical and business teams (6+ members).
• Strong understanding of AI governance, responsible AI principles, and data privacy or compliance requirements.
• Experience overseeing business analysis and translating requirements into AI use cases and solutions.
• Knowledge of AI security best practices and compliance frameworks.
• Track record of driving AI adoption and organizational change management.
• Strong communication skills with technical and non‑technical stakeholders at all levels.

• Hands‑on experience with GenAI products, AI agents, or LLM‑powered applications in production.
• Familiarity with AI orchestration frameworks:
  Lang Chain, Llama Index, Semantic Kernel, or Auto Gen.
• Experience designing and delivering AI training or enablement programs internally and for clients.
• Exposure to AI QA methodologies, including model evaluation and output validation.
• Experience with enterprise BI platforms (e.g., Microsoft Fabric, Power BI) and lakehouse architectures.
• Background in managed services, shared services, or consulting environments.
• Certifications in AI, cloud platforms (AWS/Azure), or project management (PMP, PMI‑ACP).