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.
Key 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).
Preferred Qualifications
- 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