Agile Project Manager

Avetta, LLC

2d•$114,000 - $128,000•Hybrid

About The Position

Avetta is evolving from traditional Agile and SAFe delivery frameworks to an AI-Augmented Product Development Lifecycle (AI-PDLC), where AI agents assist throughout product development and humans retain ownership of key decisions. The Agile Project Manager is responsible for coordinating delivery across the pipeline and ensuring that appropriate human judgment and approval are applied at each gate before work advances. The role works with product and engineering pods, coordinates cross-team initiatives, maintains delivery metrics and records, and supports teams as the AI-PDLC framework develops. Candidates residing within 30 miles of an Avetta office must work a hybrid schedule of three days in the office and two days from home each week. Candidates residing more than 30 miles from an Avetta office may be considered for remote employment.

Requirements

3–5 years of experience in Agile delivery, project management, or program coordination in a SaaS or software environment.
Hands-on experience working with cross-functional teams, including Product, Engineering, QA, and Design.
Solid understanding of Agile/Scrum frameworks and ability to adapt ceremonies to AI-augmented team models.
Familiarity with Spec-Driven Development and the relationship between input spec quality and AI output quality.
Working knowledge of Human-in-the-Loop gate concepts and the distinction between AI-generated artifacts and human-owned decisions.
Proficiency with Jira, Scriptrunner, Confluence, and Aha! for initiative tracking, gate logging, and reporting.
Comfortable using Microsoft Teams and SharePoint for distributed team collaboration.
Strong written and verbal communication skills, including the ability to translate AI pipeline status into clear, business-relevant updates.
High judgment and organizational discipline, with the ability to manage multiple initiative workstreams while maintaining gate integrity.
Collaborative and proactive approach, with the ability to influence without direct authority.
Openness to rapid iteration as the AI-PDLC framework matures.
Bachelor's degree in Business Administration, Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience in Agile delivery or program coordination.

Nice To Haves

Experience in an organization undergoing Agile or technology transformation.
AI-augmented delivery experience.
Experience with AI productivity tools such as Atlassian Intelligence, Glean, Claude, or equivalent.
SAFe or AI fluency credentials, including SA, SSM, SASM, SPC, AWS AI Practitioner, or Google AI Essentials; these are weighted above traditional PM certifications.
Traditional PM certifications such as CSM, PSM I–II, CAPM, or PMP.

Responsibilities

Own end-to-end delivery flow for one or more initiatives across the five-zone AI-PDLC pipeline, from validated discovery through production release.
Track initiative progress using the three Red Box milestones—pipeline entry, approved spec, and production—and monitor cycle time and throughput.
Coordinate handoffs between pipeline zones and ensure required sign-offs are in place before AI-generated artifacts advance.
Facilitate the Spec Agreement gate, where the Product Manager and Tech Lead confirm intent and approach before AI-assisted coding begins.
Maintain a Gate Decision Log in Confluence for each initiative, recording reviews, decisions, and changes.
Identify missing or incomplete dependencies early and ensure prerequisites are available before AI coding proceeds.
Coordinate across delivery pods of three to five people and integrate work spanning multiple teams, domains, or codebases.
Facilitate cross-pod syncs focused on AI pipeline blockers, spec quality, and handoff readiness.
Own initiative-level RAID and decision logs, including attention to unresolved spec questions and AI output drift.
Partner with Scrum Masters to identify and escalate pod-level blockers before they become pipeline bottlenecks.
Serve as the primary communication point among Product Management, engineering pod leads, Release Management, and senior stakeholders.
Prepare concise, data-driven monthly C-level updates on pipeline volume, spec approval rate, and production throughput.
Communicate spec quality issues and AI agent output concerns with proposed mitigations.
Help Product Managers set stakeholder expectations for AI-PDLC timelines.
Apply the Spec Rubric at the approved-spec gate and prevent work from advancing below the agreed quality standard.
Identify and report spec rejection patterns as early-warning indicators of downstream delivery slowdowns.
Ensure Definition of Ready criteria are met before initiatives enter the delivery zone.
Track and ensure resolution of open spec questions across initiatives.
Maintain delivery data in Jira, Aha!, and Confluence, including accurate gate timestamps for cycle-time reporting.
Build and maintain dashboards for cycle time, throughput, spec rejection rate, PR review cycles, and human gate hours per initiative.
Use AI productivity tools to reduce manual tracking and proactively surface blockers.
Coach pod teams and stakeholders on AI-PDLC expectations, Human-in-the-Loop gate responsibilities, and productive engagement with AI agents.
Champion the principle that AI generates artifacts while humans own decisions.
Contribute observations and improvement ideas to the evolving AI-PDLC framework.