Delivery Lead, AI-Driven Price Optimization

Zelis

Boston (MA)

Hybrid

USD 115,000 - 145,000

Full time

14 days+

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Job summary

Zelis is seeking a Delivery Lead to own delivery health for an assigned product area within Price Optimization. You will track initiatives, surface risks, and align product, technology, and operations on priorities and expectations.

As a portfolio-level operator, you will coordinate with product management and engineering leadership, ensuring right work is sequenced and delivered with quality. Strong skills in AI tools and Atlassian suite are required.

Qualifications

8+ years in program management, delivery operations, portfolio management, or related field, Master's degree may substitute for up to 2 years of experience.
Experience managing delivery across a portfolio of concurrent initiatives with tracking, reporting, and risk management.
Proficiency using AI tools in day-to-day work, including prompts development and evaluation of outputs.
Hands-on experience with the Atlassian suite (Jira, Confluence, Jira Product Discovery) and SDLC frameworks (Agile, Scrum, Kanban, SAFe).
Strong stakeholder management skills and ability to align priorities with senior leaders.

Responsibilities

Own delivery status across all active initiatives within the assigned product area, tracking progress, risks, and dependencies.
Maintain a clear view of in-flight work, risks, and items needing leadership attention.
Prepare and facilitate delivery status reviews with senior stakeholders including product and technology leaders.
Ensure commitments are realistic when made and visible when at risk.
Establish and maintain a delivery reporting cadence to provide insights with minimal manual effort.
Partner with product managers to prioritize the initiative portfolio and align delivery sequencing to business value.
Work with technology leads to understand capacity, dependencies, and technical risk before they affect delivery.
Serve as the connective tissue between product intent and engineering execution.
Engage cross-functional stakeholders to align expectations and communicate delivery progress clearly.
Escalate risks with context and recommended paths forward.
Apply PDLC standards at intake to reduce late-stage discovery and churn.
Identify intake quality patterns and resolve them upstream with product and engineering.
Monitor initiative readiness and coordinate delivery planning cycles.
Flag intake gaps before they cause disruptions.
Identify process gaps and operational inefficiencies and implement improvements.
Build and maintain delivery dashboards and reporting artifacts in Jira and other tools.
Define consistent standards for work tracking, reporting, and escalation across multiple teams.
Champion data quality in Jira for trustworthy reporting.
Identify and implement AI tools that reduce manual overhead in delivery tracking and reporting.