Senior Manager - Engineering Excellence

About the Role:

Manhattan Associates is looking for a Senior Manager - Engineering Excellence to improve how engineering works across the end-to-end software development lifecycle.

This is a broad, horizontal Engineering Excellence role. It will work across engineering, product, architecture, DevOps, security, quality, operations, and delivery teams to improve how teams plan, build, integrate, test, release, and operate software.

A core responsibility is to establish a common engineering measurement and improvement system that connects demand, commitments, capacity, engineering flow, quality, productivity, technical debt, reliability, developer experience, and delivery outcomes.

Quality Engineering and Test Automation are important components of the role, but the broader focus is balanced Engineering Effectiveness - including engineering flow, developer productivity, delivery predictability, technical debt, DevOps/DevSecOps, engineering standards, AI-assisted engineering, and continuous improvement.

The role will initially operate largely through influence across existing engineering teams rather than through direct ownership of a large delivery organization. Existing engineering managers will continue to own their teams and delivery commitments.

Success will be demonstrated through measurable improvements in speed, quality, predictability, productivity, reliability, technical debt, and developer experience.

What this role is - and is not

This role is

• A horizontal engineering-improvement capability across multiple teams.
• A technically credible role that uses data and engineering metrics to identify constraints & guide change.
• A role that improves the whole engineering system, not one function in isolation.
• A capability-building role that works through influence, enablement, standards & measurable outcomes.

This role is not

• A QA or Test Automation leadership role.
• A Platform Engineering, DevOps, or SRE-only role.
• A PMO or Technical Program Management role.
• An application delivery manager role.

What you will do

Build the engineering measurement and improvement system

• Establish a common baseline for engineering health across relevant teams, while allowing for differences in technology, products, and maturity.
• Design and use cross-team engineering metrics, scorecards, and dashboards that connect demand, commitments, capacity, flow, quality, productivity, technical debt, reliability, and delivery outcomes.
• Use DORA metrics or equivalent measures - such as cycle time, lead time, throughput, deployment frequency, change failure rate, recovery time, and predictability - where they are appropriate.
• Use measures to identify constraints, guide trade-offs, prioritize interventions, and demonstrate improvement - not simply to report activity.
• Avoid vanity metrics or measures that create the wrong behaviors; focus on team and system outcomes rather than individual activity.

Improve engineering flow and delivery effectiveness

• Identify bottlenecks across planning, development, integration, testing, release, and production.
• Lead targeted interventions that reduce wait states, rework, manual handoffs, dependencies, release friction and avoidable process variation.
• Demonstrate measurable improvements in engineering speed, quality, predictability, productivity, reliability or developer experience.
• Create meaningful visibility into engineering health, constraints, risks, and improvement priorities for engineering and business leaders.

Strengthen the end-to-end SDLC operating model

• Design and improve workflows from demand intake and prioritization through development, integration, QA, UAT, production release, and operational feedback.
• ▪ Define practical ownership models, entry and exit criteria, quality gates, handoffs, and escalation paths.
• ▪ Establish scalable ways of working while allowing teams appropriate flexibility based on product, technology & risk.

Improve capacity, productivity, and technical-debt management

• Improve visibility into engineering capacity and allocation across roadmap commitments, BAU work, defects, reliability, technical debt, and improvement initiatives.
• Help leaders make informed trade-offs between feature delivery, quality, modernization, operational health, and long-term maintainability.
• Establish practical ways to identify, quantify, prioritize, and track technical debt based on business risk and engineering impact.
• Lead initiatives that improve developer productivity, developer experience, engineering focus, and time to value.
• Identify systemic constraints affecting collaboration, onboarding, flow, and engineering effectiveness.

Advance DevOps, DevSecOps, and engineering standards

• Partner with Platform Engineering, DevOps, Security, Architecture, and development teams to strengthen CI/CD,automation, release management, observability, and secure software delivery.
• Define common engineering standards, reference practices, maturity models, and reusable capabilities.
• Promote automation and self-service mechanisms that reduce manual effort and improve consistency.
• Support adoption through enablement, coaching, communities of practice, and measurable outcomes.

Advance Quality Engineering & Test Automation

• Provide strategic direction for Quality Engineering, Test Automation, shift-left quality, testability, and risk-based validation.
• Strengthen automation frameworks, quality gates, test environments, and feedback loops across the delivery lifecycle.
• Integrate quality practices into development and delivery rather than treating quality as a separate downstream activity.
• Use quality, defect, escaped-defect, and release-risk insights as part of the broader engineering improvement system.

Enable AI-assisted engineering and continuous improvement

• Identify and scale responsible AI use cases across requirements, design, development, code review, testing, documentation, release, and operations.
• Measure AI adoption through meaningful productivity, quality, cycle-time, or developer-experience outcomes.
• Establish reusable patterns, enablement, and guardrails for AI-assisted engineering.
• Build a culture of experimentation, learning, retrospection, and measurable improvement.

Lead through influence

• Build alignment across engineering leaders and teams around shared outcomes, standards, and improvement priorities.
• Influence without direct reporting authority through data, credibility, facilitation, coaching, and stakeholder management.
• Create reusable playbooks and communities of practice that scale beyond individual teams.
• Communicate complex engineering topics clearly to senior technical and business stakeholders

Core requirements

The following capabilities are essential for this role:

• 14+ years of experience with strong software-engineering, engineering-enablement, DevOps, platform engineering, Quality Engineering, or comparable technical foundation.
• Demonstrated experience improving engineering outcomes across multiple teams - not only managing delivery, testing, automation, platform operations, or program execution within one function.
• Demonstrated experience designing and using cross-team engineering metrics, scorecards, or dashboards to identify constraints, guide trade-offs, and drive measurable improvement - not simply report activity.
• Experience establishing a baseline, identifying bottlenecks, implementing interventions, and demonstrating measurable improvement in engineering flow or delivery outcomes.
• Experience improving end-to-end SDLC workflows spanning development, integration, testing, CI/CD, release, and production feedback loops.
• Strong understanding of demand, commitments, capacity allocation, delivery predictability, developer productivity, technical debt, and engineering trade-offs.
• Experience connecting demand, commitments, capacity, delivery flow, quality, and outcomes across engineering teams.
• Technical credibility across modern CI/CD, DevOps/DevSecOps, software delivery, Quality Engineering, and engineering automation practices.
• Experience establishing common engineering standards, maturity models, reusable practices, or cross-team operating mechanisms.
• Demonstrated ability to influence engineering teams and senior stakeholders without relying on formal authority.
• Strong analytical, communication, facilitation, and change-leadership skills.

Four capabilities we will specifically assess

• Engineering measurement: Can establish a baseline, identify a constraint, lead an intervention, and prove the improvement.
• Horizontal influence: Has changed engineering practices across teams outside their direct reporting line.
• End-to-end SDLC breadth: Understands and has improved the full flow from demand and development through testing, release, production, and feedback.
• Demand, capacity, and technical debt: Can connect incoming demand and commitments with available capacity and make engineering trade-offs visible.

The profile we are looking for

• You may come from Engineering Excellence, Engineering Productivity, Developer Experience, Engineering Enablement, Platform Engineering, DevOps/DevSecOps Transformation, Engineering Operations, Quality

Engineering transformation, or a comparable engineering leadership background.

• The strongest candidates will combine technical engineering depth with the ability to improve processes, operating models, metrics, productivity, quality, technical debt, and adoption through influence.