AI Enablement and Agile Coaching

Responsibilities

• A. Delivery Enablement
• Enable outcome-driven delivery
• Coach teams and product partners to focus on measurable outcomes, clear goals, and iterative value delivery-avoiding process for process's sake.
• Remove systemic blockers
• Identify and resolve impediments across process, organization, dependencies, tooling, and operating model.
• Facilitate decisive alignment
• Lead high-impact planning, prioritization, dependency mapping, and retrospectives with a strong bias toward decisions and action.
• Drive data-informed improvement
• Use delivery and flow metrics to surface bottlenecks and anti-patterns, translating insights into practical improvement plans.
• Influence through transparency
• Communicate risks, progress, and systemic themes to leadership; influence without authority through evidence, narrative, and trust.
• Contribute to standards and playbooks
• Identify patterns and codify lightweight guidance that improves consistency while respecting context.
• B. GenAI Accelerator Enablement
• (Foundational focus: rapid, practical agents-not deep R&D)
• Prompt engineering for outcomes
• Design, test, and refine prompts and system instructions that reliably support delivery and operational use cases (e.g., summarisation, drafting, extraction, Q&A, planning).
• Prototype lightweight agents
• Build targeted, fit-for-purpose agents that streamline repetitive work and improve responsiveness (e.g., intake triage, status synthesis, decision logs, release notes) using enterprise guardrails.
• Basic tool-using agents
• Configure agents to safely use approved tools and connectors, following governed tool-calling patterns.
• Governance by design
• Ensure agent prototypes align with enterprise expectations as they mature-registration, lifecycle management, and appropriate risk and control checkpoints.
• Quality and evaluation
• Establish lightweight testing practices (accuracy checks, hallucination controls, traceability) before broader adoption.
• Upskill and enable others
• Coach teams and partners on prompt quality, limitations, and responsible use, including human-in-the-loop practices and bias awareness.
• Required Qualifications, Capabilities, and Skills
• 8+ years in delivery enablement, agile delivery, product operations, program execution, or equivalent experience coaching teams in complex environments.
• Pragmatic experience across delivery approaches (e.g., Scrum, Kanban, XP-informed practices, scaling patterns).
• Strong stakeholder leadership: facilitation, influencing, executive communication, and comfort with ambiguity.
• Proven use of metrics and evidence to drive improvement (flow, predictability, quality, and/or operational KPIs).
• Foundational GenAI fluency: understands LLM strengths and limits; able to craft prompts and prototype simple agent workflows.
• Comfortable partnering with engineers and conversant in modern engineering practices (CI/CD, testing, APIs, cloud concepts).

Requirements

• Formal training or certifications in coaching, agile, or change leadership.
• Experience building proof-of-concepts using low-code/no-code tools or lightweight scripting; basic Python or JSON helpful but not required.
• Familiarity with enterprise agent concepts, including governance, guardrails, traceability, and secure tool access patterns
• Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

Additional Information

Join us as a Transformation AI Enablement Lead , where you'll coach outcome-driven delivery, remove systemic blockers, and design safe, pragmatic GenAI agents that improve productivity, decision quality, and transparency.

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Company Intel

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