AI-Native Senior Engineering Manager, Full Stack

PwC is a leading firm focused on software and product innovation, seeking an AI-Native Full Stack Senior Engineering Manager to lead the modernization and cloud transformation of legacy workloads into cloud-native AWS solutions. The role involves defining AI-native engineering strategies, mentoring teams, and driving efficiency through AI tool adoption and cloud solutions.

Responsibilities:

• Lead assessment, planning, and execution of full stack application migrations to AWS
• Analyze existing application portfolios for cloud readiness, dependencies, and modernization opportunities
• Architect end-to-end migration solutions including re-hosting, re-platforming, and refactoring of front-end, back-end, and data components
• Design AWS-native architectures using Lambda, EC2, ECS/EKS, API Gateway, RDS, DynamoDB, S3, CloudFront, Cognito, and IAM
• Develop Infrastructure as Code using Terraform, CloudFormation, or AWS CDK
• Implement CI/CD pipelines incorporating AI-powered code quality gates, automated security scanning, and AI-assisted deployment validation
• Define and drive AI-native engineering strategy across teams, establishing standards for AI tool adoption, measuring productivity gains, and reporting efficiency metrics to leadership
• Lead and mentor engineering teams on modern development frameworks (React, Angular, Vue.js) and backend technologies (Node.js, Java, Python) with AI-augmented workflows as the default
• Design applications with AI agent integration points, evaluating and architecting agentic AI solutions within modernization and migration initiatives
• Implement AWS security best practices and govern identity, compliance, and networking
• Collaborate with DevOps, Security, QA, and business teams for delivery excellence
• Use CloudWatch, X-Ray, and CloudTrail for observability and performance optimization
• Evaluate emerging AI development tools and platforms; set adoption strategy and measure ROI for the engineering organization
• Maintain architecture and migration documentation
• Use AI coding assistants (GitHub Copilot, Cursor, Claude Code, Codex, Kiro) as your default development workflow and define the AI-native engineering strategy for the organization
• Evaluate emerging AI development tools and platforms; set adoption strategy and measure ROI
• Establish organization-wide standards for AI-assisted development, code review, testing, and deployment
• Drive measurable efficiency gains through AI tool adoption and report metrics to leadership
• Architect applications with AI agent integration points, leveraging agentic AI frameworks (LangChain, Claude Agent SDK, Bedrock Agent SDK)
• Mentor engineering leaders and teams on AI-native practices as the standard operating model