Agile Execution Coach

The Hartford•Hartford, CT

18h•Hybrid

About The Position

The Agile Center of Enablement is accountable for advancing delivery excellence across the enterprise through execution enablement, coaching, AI-enabled ways of working, and organizational effectiveness. The Agile Execution Coach partners across business and technology to accelerate value delivery, improve transparency, and support modern operating model adoption. 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). As AI accelerates delivery and increases solution complexity, including agentic and non-deterministic behaviors, organizations are placing greater emphasis on execution excellence, decision quality, governance clarity, and measurable business outcomes. Modern Agile Execution Coaches help leaders and teams improve delivery performance through AI-enabled ways of working, data-driven decision making, and operating models that accelerate the flow of value from strategy to execution.

Requirements

Exceptional communication, influencing, leadership, facilitation, and problem-solving skills.
Demonstrated experience coaching teams, leaders, programs, and organizations.
Strong understanding of Agile frameworks, including Scrum, Kanban, and SAFe.
Experience improving delivery predictability, organizational effectiveness, and execution outcomes.
Experience using metrics, dashboards, reporting, and analytics to support decision making and continuous improvement.
Demonstrated fluency using AI copilots, AI-enabled productivity tools, and AI-assisted workflows.
Understanding of responsible AI practices, governance, controls, and enterprise adoption approaches.
Experience leading organizational change and transformation initiatives.
Strong coaching, mentoring, teaching, and facilitation skills.
Five or more years of Agile delivery, coaching, program leadership, portfolio leadership, or related experience.
Candidate must be authorized to work in the US without company sponsorship.
The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Nice To Haves

Knowledge of Lean Portfolio Management, Product Operating Models, Agile Engineering Practices, DevOps, and modern software delivery approaches is preferred.
Agile or SAFe certifications are preferred.

Responsibilities

Align strategy to execution by translating enterprise priorities into actionable team, program, and portfolio delivery plans.
Improve delivery outcomes through coaching, facilitation, execution management, and continuous improvement practices.
Enable end-to-end delivery by promoting consistent ways of working, planning practices, delivery governance, and execution discipline across teams and value streams.
Strengthen governance and transparency through meaningful metrics, reporting, dashboards, and leadership insights.
Coach leaders and teams on Agile, Product, Portfolio, and AI-enabled ways of working.
Advance AI Operating Model adoption by helping teams incorporate AI capabilities into planning, delivery, reporting, governance, and operational workflows.
Leverage AI copilots and accelerators to improve productivity, coaching effectiveness, insight generation, and organizational learning.
Use AI-assisted analysis to identify trends, risks, bottlenecks, decision delays, and improvement opportunities.
Identify and remove impediments, execution risks, and organizational constraints that limit the flow of value.
Facilitate alignment across business, product, engineering, architecture, risk, data, and enabling functions.
Enable effective planning, prioritization, dependency management, and decision making at team, program, and portfolio levels.
Deliver training, onboarding, workshops, office hours, and community-of-practice activities that strengthen organizational capability.
Build reusable playbooks, prompt libraries, coaching frameworks, and enablement assets that scale knowledge and adoption across the enterprise.
Drive continuous improvement through data-driven insights, retrospective learning, and outcome-based measurement.