Senior Manager, AWS Full Stack AI Engineering

PwC•Tampa, FL

23h•$124,000 - $280,000

About The Position

As a Senior Manager, AWS Full Stack AI Engineering, you will lead multidisciplinary teams in designing, building, testing, and maintaining AI-enabled applications across the software development lifecycle within PwC’s Advisory practice. You will lead large projects, exercise sound judgment in complex situations, and use technical and business knowledge to guide teams, shape delivery approaches, and support strategic client conversations. You will help shape cloud-native solutions on AWS, modernize legacy applications, and coordinate architecture, development, testing, and deployment across technology stacks, programming languages, and tools.

Requirements

At least a bachelor's degree.
At least 7 years of experience.

Nice To Haves

Preference for study in at least one of these fields: Accounting; Analytics/Data Science; Artificial Intelligence/Robotics; Business Administration/Management; Computer Science/Information Systems; Design/Multimedia; Engineering; Operations/Supply Chain; or Project/Technology Management.
Experience leading AWS-native development and testing initiatives.
Cloud engineering knowledge across architecture and platform delivery.
Ability to apply AI fluency to modern application and solution architecture.
Ability to translate business needs into scalable, cloud-based technical designs.
Clear communication with clients and diverse stakeholders through complexity.

Responsibilities

Lead AWS full stack AI engineering initiatives from discovery through delivery across cloud-native application and testing workstreams.
Design scalable application and solution architectures that combine AI-native techniques, AWS services, and modern development patterns.
Guide technical teams through requirements definition, architecture planning, build activities, and validation for greenfield and modernization efforts.
Advise clients on platform engineering choices, integration patterns, and cloud infrastructure tradeoffs that shape delivery outcomes.
Coordinate architecture reviews across security, network design, infrastructure, and cloud service considerations.
Translate business objectives into technical roadmaps connecting software design, testing strategy, and deployment readiness.
Apply AI fluency and analytical thinking to identify opportunities for rapid experimentation and process improvement.
Evaluate application performance, reliability, and security issues across the software development lifecycle.
Develop client-ready communications that explain technical decisions, risks, and delivery options clearly.
Coach teams to solve complex engineering problems while maintaining operational excellence across multiple workstreams.