AI-Native Engineering Lead, Full Stack - Manager

PwC•Cincinnati, OH

2d•$99,000 - $232,000

About The Position

At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. Those in software engineering at PwC will focus on developing innovative software solutions to drive digital transformation and enhance business performance. In this field, you will use your knowledge to design, code, and test cutting-edge applications that revolutionise industries and deliver exceptional user experiences. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Analyse and identify the linkages and interactions between the component parts of an entire system. Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion. Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables. Develop skills outside your comfort zone, and encourage others to do the same. Effectively mentor others. Use the review of work as an opportunity to deepen the expertise of team members. Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
7+ years of IT experience including extensive software development and application architecture.
Minimum 3 years of hands-on experience with AWS cloud solutions, focusing on application migration and modernization.
Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, Claude Code, Codex, or Kiro) with demonstrated ability to improve team productivity through AI tool adoption.
Experience measuring and reporting AI-driven productivity improvements across engineering teams.
Familiarity with agentic AI frameworks including LangChain, Claude Agent SDK, and Bedrock Agent SDK, and their application in the SDLC.
Understanding of AI agents in development workflows (automated code review, deployment agents, testing agents).
Strong full stack development skills with front-end (React, Angular, Vue.js) and back-end (Node.js, Java, Python, .NET) frameworks.
Experience migrating monolithic, legacy, or on-premises applications to AWS (lift-and-shift, re-platforming, refactoring).
Deep knowledge of AWS services: EC2, Lambda, ECS/EKS, API Gateway, RDS, DynamoDB, S3, Cognito, CloudWatch, IAM.
Strong skills in Infrastructure as Code (CloudFormation, Terraform, CDK).
Proficient with containerization and orchestration (Docker, Kubernetes, AWS ECS/EKS).
Experience setting up automated CI/CD pipelines (AWS CodePipeline, Jenkins, GitLab CI).
In-depth understanding of microservices architecture, serverless paradigms, and event-driven design.
Solid experience in application security best practices on AWS.
Excellent analytical, communication, and stakeholder management skills.
Proven success in leading cloud migration projects impacting multiple application layers.

Nice To Haves

AWS Certifications such as AWS Certified Solutions Architect — Professional, AWS Certified DevOps Engineer, or AWS Certified Developer.
Experience with migration tools like AWS Application Migration Service (MGN), AWS Server Migration Service (SMS), or Database Migration Service (DMS).
Familiarity with cloud cost management and performance optimization post-migration.
Exposure to Agile/Scrum methodologies.
Experience with enterprise-scale applications and multi-account AWS environments.
Knowledge of legacy technologies (e.g., .NET Framework, Java EE, Oracle DB).

Responsibilities

Lead architecture and technical strategy for migrating legacy and on-premises applications to AWS cloud.
Assess existing application architectures and codebases for cloud readiness and modernization opportunities.
Design scalable, secure, and automated migration solutions for full stack applications (front-end, back-end, data layers).
Implement application refactoring, re-platforming, or re-architecting efforts to leverage AWS native services (e.g., Lambda, ECS/EKS, RDS, DynamoDB).
Develop front-end and back-end architectures ensuring seamless integration and cloud compatibility.
Define cloud infrastructure using Infrastructure as Code (IaC) tools such as AWS CloudFormation, Terraform, or AWS CDK.
Create and maintain CI/CD pipelines for continuous integration and automated deployments, incorporating AI-powered code quality gates and automated security scanning.
Lead and mentor development teams on AI-native engineering practices, establishing standards for AI tool adoption and measuring productivity gains across modern development frameworks and backend technologies.
Collaborate with cross-functional teams including DevOps, security, QA, and product to ensure successful migration and operation.
Develop and enforce cloud migration best practices, security policies, and governance.
Evaluate and integrate agentic AI solutions into development and deployment workflows to drive automation and efficiency.
Identify and mitigate risks associated with migration activities.
Monitor migrated applications for performance, cost optimization, and security compliance on AWS.
Stay current with AWS migration tools, AI development tools, and cloud-native patterns to continuously improve approach.
Use AI coding assistants (GitHub Copilot, Cursor, Claude Code, Codex, Kiro) as your default development workflow and set standards for team adoption.
Measure and report AI-driven productivity improvements across your engineering team.
Mentor engineers on effective AI-assisted development patterns, prompt engineering, and AI tool workflows.
Evaluate AI agents and automation tools for integration into development, testing, and deployment pipelines.
Establish team norms for AI-assisted code review, test generation, and documentation.