AI Lead with Scrum Master || Mexico (Remote)

Job Title :: AI Lead with Scrum Master

Location :: Mexico (Remote)

Job Type :: Contract

Role Overview

This role sits at the intersection of delivery leadership, AI-augmented workflow orchestration, and team development. The Kanban / Agentic AI Task Master is responsible for managing the end-to-end flow of engineering work from intake to delivery while leveraging agentic AI tooling to accelerate throughput, reduce friction, and surface blockers before they become delays. This person leads with both a Dev Manager's accountability mindset and a Scrum Master's servant-leadership model.

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Core Responsibilities

Flow & Delivery Management

• Own and continuously optimize the Kanban system across all active workstreams: Backlog, WIP limits, queue management, cycle time, and throughput metrics

• Eliminate blockers proactively; escalate impediments with urgency and own resolution

• Maintain a healthy, prioritized backlog in partnership with Product and stakeholders

• Drive on-time delivery against committed dates with zero tolerance for silent slippage

• Define and enforce Definition of Ready and Definition of Done standards

Agentic AI Orchestration

• Maintain team usage of the public agentic AI workflows that automate repetitive task tracking, status updates, sprint hygiene, and reporting

• Leverage agentic tooling to manage the ADO backlog and delivery schedule to internal and external stakeholders.

• Identify high-friction manual processes and build agent-driven solutions to replace them

Dev Manager Responsibilities

• Hold the team accountable to delivery commitments — dates set by the team are firm

• Manage individual performance against defined objectives; conduct regular 1:1s and feedback cycles

• Partner with Engineering leadership on headcount, hiring, and team structure

• Remove organizational obstacles that impede team velocity

• Own team-level OKRs and report progress with transparency to leadership

Scrum Master

• Facilitate daily standups, retrospectives, and planning sessions with active engagement that ensures each team member clearly articulates next steps, expected outcomes, and any blockers. Passive status reporting is not sufficient; sessions should drive alignment, accountability, and forward progress.

• Coach team members on Kanban principles, flow efficiency, and continuous improvement

• Shield the team from unplanned interruptions while maintaining stakeholder alignment

• Challenge the team/resources to maintain quality, delivery, and velocity that were committed to

• Require active participation from all resources in sprint activities

• Champion process improvements surfaced in retros and drive them to completion

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Key Objectives

• Reduce average cycle time by measurable increments quarter over quarter

• Achieve 95%+ on-time delivery rate against committed dates within 90 days

• Implement at least two agentic AI workflow automations per quarter that demonstrably reduce manual overhead

• Maintain team health scores and engagement above baseline through active coaching and support

• Build and maintain a real-time delivery dashboard visible to all stakeholders

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Skills & Qualifications

• 7+ years in engineering delivery roles — Scrum Master, Delivery Lead, Engineering Manager, or equivalent

• Deep fluency in Kanban methodology; experience with flow metrics (cycle time, lead time, CFDs)

• Hands-on experience with agentic AI tools, LLM-based automation, or prompt engineering in a delivery or scrum team context — and a track record of driving adoption across a team, not just personal use

• Strong proficiency with project tooling — ADO

• Demonstrated ability to lead without direct authority and influence cross-functional teams, including technical leads and QA — ensuring accountability is shared, not absorbed

• Direct communicator who escalates early, surfaces problems without spin, and proactively informs leadership of delivery risks before they become surprises — with a mitigation plan already in motion

• Naturally owns risk across time zones and off-hours — does not allow a Friday blocker on a Monday deadline to go unaddressed over the weekend

• Treats Definition of Done as a real gate — enforces pre-delivery verification with the team rather than discovering gaps in production or during a war room

• Comfortable operating at the intersection of process discipline and people coaching — knows when to tighten the system and when to develop the person

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What Success Looks Like

• At 30 days — full command of current board state, all active blockers named and owned, first AI workflow automation scoped, and a clear picture of where team habits are strong vs. where they need coaching.

• At 60 days — cycle time baseline established, team cadences running cleanly, first agent automation live, and zero instances of a delivery risk reaching leadership as a surprise

• At 90 days — measurable throughput improvement, delivery predictability at or above target, team AI adoption visibly increasing, stakeholder confidence high, and technical leads operating as true co-owners of delivery milestones rather than passive participants