Project Lead, Delivery

Overview

The Technical Project Lead (TPL) is the hands-on technical leader embedded within Walmart delivery programs. The TPL builds a working understanding of the client environment, translates architecture and acceptance expectations into executable standards, validates milestone readiness, and coaches consultants toward high-quality delivery. The role bridges Walmart technical leadership, Insight Global consultants, and the Project Manager so that technical progress is accurate, risks are visible early, and deliverables are ready before they reach the client.

This role does not replace the Project Manager. The Project Manager owns integrated planning, schedule, budget, stakeholder communication, and program reporting; the TPL owns the technical truth that informs those activities.

Responsibilities

1. Walmart Environment & Architecture Fluency

• Engage Walmart technical leaders at the start of each program to understand the current-state and target architecture, engineering practices, security and quality expectations, release pathways, and technical definition of done.

• Map where Insight Global resources and deliverables fit within the broader architecture, including upstream and downstream dependencies, Walmart-owned components, other vendors, platform teams, and approval points.

• Maintain current technical context as architecture, priorities, standards, or dependencies change; translate changes into clear actions and impacts for consultants and the Project Manager.

• Navigate Walmart's large-scale, cross-team environment with discipline, curiosity, and respect for client governance, tooling, code review, and technical decision-making processes.

• Decompose each technical milestone into the work steps, dependencies, review gates, required evidence, and acceptance criteria needed to demonstrate completion.

• Maintain a milestone tracker or approved single source of truth that shows current state, remaining work, technical owner, dependencies, evidence, blockers, and readiness status.

• Learn from Walmart pull request reviews, technical manager feedback, defects, and prior decisions; convert recurring feedback into explicit acceptance criteria and consultant standards.

• Review milestone deliverables before client release and confirm technical completeness, accuracy, integration readiness, test evidence, and alignment with agreed scope and architecture.

• Never treat percent complete as sufficient evidence; validate what is built, reviewed, tested, integrated, approved, and still outstanding.

• Identify technical risks early, including architectural gaps, unclear requirements, cross-team dependencies, environment constraints, review bottlenecks, quality issues, and unrealistic sequencing.

• Explain risk in delivery terms: what is happening, why it matters, milestone or release impact, mitigation options, decision required, owner, and target date.

• Validate designs, technical decisions, integrations, code or configuration approaches, test strategies, and implementation plans at the depth appropriate to the engagement.

• Escalate promptly when evidence does not support the stated status or when the team cannot resolve a blocker within the agreed path.

• Meet consultants early to understand their strengths, development areas, confidence, and likely delivery risks; use this insight to recommend task alignment, coaching, and targeted support.

• Hold a weekly technical team cadence covering current milestones, blockers, cross-team coordination, Walmart feedback, lessons learned, engineering quality, and responsible AI usage and prompting practices.

• Conduct regular one-on-one working sessions or work reviews with a rotating set of consultants to understand day-to-day execution, uncover hidden challenges, gather technical insight, and build trust.

• Coach consultants through technical challenges and reinforce reusable engineering patterns, documentation discipline, and quality expectations without becoming the default executor for the team.

• Provide evidence-based technical performance observations to delivery leadership while partnering with the appropriate people leader on formal performance management.

• Meet with the Project Manager at least weekly to review completed work, work in progress, milestone readiness, risks, blockers, dependencies, decisions, and support needed.

• Provide a concise weekly technical recap that the Project Manager can incorporate into client reporting; ensure the technical narrative is accurate, evidence-based, and easily understood.

• Review SOWs, Project Change Orders, status updates, Quarterly Business Reviews content, and recovery plans for technical scope, assumptions, feasibility, dependencies, and accuracy.

• Participate in consultant interviews and technical onboarding; support client technical conversations when depth, clarification, or risk resolution is required.

• Document material technical decisions, consultant observations, and risks in the designated system of record.

• 5+ years of experience in software engineering, cloud, data, platform, infrastructure, quality engineering, AI, architecture, or a related technical delivery discipline.

• Demonstrated experience working within Walmart's technology environment, including its architecture, technical governance, engineering and review practices, cross-team dependencies, and large enterprise vendor ecosystem.

• Experience leading or guiding technical teams on complex enterprise programs and validating delivery quality across multiple contributors.

• Ability to evaluate architecture, designs, implementation approaches, code or configuration artifacts, integration behavior, test evidence, and technical readiness.

• Strong written and verbal communication skills, including the ability to translate technical details into concise risk, milestone, and decision narratives.

• Experience in Agile or iterative delivery environments and comfort operating across distributed, cross-functional teams.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.

• Technical certifications relevant to the assigned domain, such as cloud, architecture, data, security, platform, or Agile credentials.

• Consulting or professional services experience supporting large enterprise clients.

• Experience with AI-assisted engineering practices, including prompt quality, output validation, security, and responsible usage.