Engineering Director, Google Cloud

PricewaterhouseCoopers•Chicago, IL

13h

About The Position

The Engineering Director, Google Cloud will lead cloud-native application design, development, testing, and modernization efforts across Google Cloud programs within PwC’s Advisory practice. The Director sets direction for multiple workstreams, shapes client engagements, drives business growth, and guides teams through technical decisions, delivery tradeoffs, and changing client needs while promoting quality, inclusion, and integrity. The role combines software engineering, data and analytics, and Generative AI capabilities to help clients build scalable solutions and modernize legacy applications. It guides solutions from concept through architecture, build, and test across a range of technologies and delivery settings. The position requires at least a bachelor’s degree and at least nine years of experience. Travel may be up to 80%.

Requirements

At least a bachelor's degree.
At least 9 years of experience.
Lead Google Cloud-native development and testing initiatives.
Build cloud-native applications across full development lifecycles.
Apply Generative AI, LLMOps, and prompt engineering.
Use Python, LangChain, LangGraph, and Vertex AI.
Drive client-facing solution design and business growth.
Mentor teams through rapid experimentation and innovation.

Responsibilities

Set strategic direction for Google Cloud-native engineering programs across AI-enabled application development and testing.
Lead client discussions to shape solution roadmaps, delivery priorities, and modernization approaches for cloud-native products.
Oversee multiple software engineering efforts from requirements through architecture, build, test, and deployment.
Drive development of generative AI solutions using Google Vertex AI, LLM APIs, LangChain, LangGraph, and retrieval-augmented generation.
Govern prompt engineering, LLM evaluation, LLM guardrails, and LLMOps practices to support reliable solution behavior.
Translate business needs into scalable cloud-native applications using Python, agent orchestration, vector databases, and digital tooling.
Advance AI-human collaboration patterns for contact center and enterprise use cases through rapid experimentation and iterative design.
Advise on architecture decisions that balance performance, maintainability, and modernization across cloud and software platforms.
Build executive-level client relationships and identify new opportunities for cloud engineering and generative AI programs.
Coach delivery teams and cultivate technical leadership across engineering, testing, and AI solution design.