Agile Coach

Requirements

• Exceptional communication, influencin

Additional Information

Agile Coach - BA07AE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future. The Agile Center of Enablement is accountable for leading the Agile transformation across the enterprise through sustained coaching models and various learning approaches. The ideal candidate has hands-on coaching experience across Agile frameworks (Scrum, Kanban, SAFe) and practical experience in an Agile role at the team, program, and/or portfolio levels. This role requires demonstrated ability to drive mindset and behavior change, strengthen delivery discipline, and evolve ways of working as the organization adopts AI-enabled delivery models. The Agile Coach will actively use AI copilots and accelerators to scale coaching (e.g., drafting working agreements, synthesizing insights, accelerating facilitation prep), while reinforcing responsible AI usage, quality standards, and controls appropriate for an enterprise environment. This role will have a Hybrid work schedule, with the expectation of working in an office (Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday). Role & Responsibilities : - Align strategy to execution by translating enterprise priorities into actionable portfolio and team ways of working - Enable end-to-end delivery by standardizing ways of working, PDLC practices, and execution consistency across teams and value streams - Advance AI Operating Model adoption by coaching leaders and teams on AI-enabled roles, practices, and delivery models; drive responsible AI usage patterns (guardrails, quality, and reuse) - Strengthen governance and metrics by delivering portfolio insights, dashboards, and data-driven decision support for leaders; use AI-assisted analysis to identify trends, risks, and improvement opportunities - Scale coaching impact with AI and enterprise tooling by leveraging AI copilots/accelerators for facilitation prep, content creation, workflow automation, and insight synthesis; establish reusable prompt patterns and coaching assets - Build enterprise capability by providing training, onboarding, and continuous skill refresh across roles (leaders, product, engineering, and delivery) - Enable AI literacy and adoption through training, clinics, and office hours (prompting basics, role-based use cases, and safe ways to apply AI within delivery workflows) - Launch new and guide existing teams through transformation by coaching leaders and teams on Agile principles, flow, and outcome-based planning - Enable program and ART execution by facilitating key events (e.g., PI planning, backlog refinement, feature/story workshops, Scrum of Scrums, retrospectives) - Identify, escalate, and help remove systemic impediments and dependencies that limit flow, predictability, and value delivery What Leading Enterprises Expect from Agile/Enterprise Coaches in the AI Era As AI accelerates delivery and increases solution complexity (including agentic and non-deterministic behaviors), enterprise coaching is shifting from primarily scaling ceremonies to strengthening decision quality, governance clarity, and outcome integrity at speed. Common expectations across the industry include: - Outcome- and decision-centric coaching: Help leaders and teams shift from activity tracking to outcome validation, clearer decision ownership, and faster learning loops - AI-enabled operating model adoption: Translate AI operating model intent into practical team behaviors (intake paths, role clarity, lifecycle expectations, and ways of working from POC → Pilot → Scale) - Advocate for disruption to legacy ways of working reinforcing agentic processes - Guardrails that preserve speed and trust: Reinforce responsible AI usage patterns by clarifying where humans must own decisions, how evidence is captured, and how teams work safely within enterprise controls - Metrics that matter in AI-accelerated delivery: Evolve measurement beyond output/throughput into signals that highlight rework, decision latency, quality, and risk escapes-using data to focus coaching where it drives enterprise outcomes - Scale enablement through reusable assets: Build repeatable playbooks, prompt patterns, role-based job aids, and communities of practice that allow consistent coaching outcomes across portfolios and teams - Reduce friction in execution: Identify and address common enterprise anti-patterns that slow AI delivery (unclear ownership/decision rights, duplicated intakes, fragmented backlogs, inconsistent tooling/cadences) - Partner across product, engineering, design, risk, and data: Coach cross-functional leaders to operate as integrated product teams: aligning roles, handoffs, and quality standards so AI solutions move from experimentation to production reliably