Manager, Technical Delivery Management

Manager, Technical Product Delivery

AI-Enabled Modernization Engineering Manager

Position Summary

The Manager, Technical Product Delivery leads one or more cross-functional software delivery teams and is accountable for delivering high-quality, secure, and reliable products from planning through production support.

This is an enhanced technical delivery leadership role with responsibility for product delivery, stakeholder alignment, people development, technical leadership, engineering modernization, and operational excellence. The Manager helps teams adopt modern, AI-enabled ways of working that improve speed, quality, and customer outcomes.

Key Responsibilities

Team and Delivery Leadership

• Lead, coach, and develop software engineers, SDETs, and other technical contributors; build high-performing, accountable, and collaborative teams.
• Own delivery of assigned product and engineering outcomes, including planning, capacity, dependencies, risks, release readiness, and stakeholder communication.
• Partner with Product, Business Analysis, Architecture, Quality, SRE, Security, Operations, and business stakeholders to translate priorities into achievable delivery plans.
• Communicate progress, risks, tradeoffs, and delivery decisions clearly to stakeholders and senior leaders.
• Foster a culture of continuous improvement through delivery, quality, operational, and customer feedback.

Technical Leadership and Engineering Modernization

• Provide technical leadership for teams building secure, scalable enterprise applications, APIs, integrations, and data-driven services.
• Guide teams in applying modern distributed-application practices, including microservices, domain-driven design, event-driven architecture, API design, integration patterns, and data-access practices.
• Partner with Architecture and platform teams on cloud, containerization, infrastructure automation, messaging, and technology improvements that support business outcomes.
• Promote strong engineering practices across the delivery lifecycle, including DevOps/DevSecOps, CI/CD, code review, automated testing, BDD, TDD, and quality engineering.
• Ensure teams build quality, security, testability, maintainability, observability, and operational readiness into delivery from the start.

AI-Enabled Engineering Leadership

• Lead practical adoption of approved AI-assisted software-development tools to improve design, coding, testing, debugging, documentation, and team effectiveness.
• Ensure AI-generated outputs are validated through established engineering practices, including code review, testing, security controls, and human accountability.
• Identify opportunities to apply AI across the software delivery lifecycle, including requirements analysis, design support, development, testing, documentation, and production support.
• Guide teams in using AI agents and workflow automation where they can improve consistency, speed, quality, or capacity.
• Partner with AI, Architecture, Security, and platform teams to enable secure, governed, and scalable AI adoption.
• Help evaluate the value of AI-enabled practices through measurable improvements in delivery flow, quality, automation, developer experience, and customer outcomes.

Production Ownership and Operational Excellence

• Ensure teams are prepared to support production services and respond effectively to issues within their areas of ownership.
• Promote reliable, observable, supportable services with appropriate monitoring, documentation, performance validation, and operational readiness.
• Partner with technical and business stakeholders to address production issues, prioritize improvements, and reduce recurrence.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; equivalent practical experience will be considered.
• Seven or more years of progressive experience in software engineering, quality engineering, or technical delivery, including delivery of customer-facing or business-critical systems.
• Three or more years of people-management experience leading technical professionals, including coaching, performance management, hiring, and career development.
• Demonstrated experience leading one or more Agile software teams and owning delivery from planning through release and production support.
• Experience leading teams delivering modern enterprise applications on the Microsoft .NET/C# technology stack.
• Working knowledge of modern application architecture, APIs and integration patterns, cloud-based applications, security controls, observability, and production-support practices.
• Experience leading modern engineering practices, including DevOps or DevSecOps, CI/CD, automated testing, BDD, TDD, code review, and quality gates.
• Experience using AI-assisted software-development tools and encouraging responsible adoption across a technical team.
• Working knowledge of AI-agent concepts, AI-enabled workflows, human-in-the-loop controls, and practical opportunities to improve the software delivery lifecycle with AI.
• Strong communication and stakeholder-management skills, including the ability to explain delivery risks and technical tradeoffs to technical and nontechnical audiences.

Preferred Qualifications

• Experience with the organization's technology ecosystem, including ASP.NET, .NET Core, C#, Web API, MVC, React, SQL Server, microservices, event-driven architecture, Kubernetes, Helm, Azure/AWS/OCI, and messaging platforms such as Azure Service Bus or RabbitMQ.
• Experience with modern test-automation tools, such as Playwright.
• Experience in healthcare, health technology, regulated industries, or environments handling sensitive data.
• Experience leading distributed teams or coordinating delivery across multiple products, services, or dependent teams.
• Experience with application, cloud, platform, or DevSecOps modernization initiatives.
• Experience configuring, prototyping, or contributing to AI agents, workflow automations, or LLM-enabled solutions.
• Familiarity with responsible-AI practices and enterprise AI governance.
• Experience using engineering metrics to improve delivery flow, quality, reliability, and team effectiveness.

What Success Looks Like

• Teams deliver commitments with predictable quality, clear stakeholder communication, and early visibility into risks.
• Technical health, quality, automation, and operational readiness improve alongside delivery outcomes.
• AI-assisted tools and automation produce measurable improvement in productivity, quality, and delivery speed while maintaining human accountability.
• Products are released with appropriate quality, security, performance, and operational readiness.
• Teams continuously improve reliability, maintainability, customer outcomes, and engineering maturity.

COMPENSATION

The salary range for this position is $150-160K. Specific offers take into account a candidate's education, experience and skills, as well as the candidate's work location and internal equity. This position is also eligible for health insurance, 401k and bonus opportunity.

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Why Claritev?

Healthcare is complex. We help make it clearer.

At Claritev, you'll do work that matters. Together, we're helping make healthcare more transparent and affordable for all through the power of data, technology, and expertise. We offer meaningful opportunities to grow your career, collaborate with talented colleagues, and make an impact on the clients and communities we serve. If you're looking for purpose, growth, and a team that succeeds together, you'll find it here.

What Guides Us

At Claritev, innovation, agility, and a focus on results drive our success. We embrace bold thinking, work as one team, take ownership, and strive for excellence in everything we do - creating meaningful impact for our clients, communities, and each other.