Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.
The Opportunity
As a Engineering Manager, Google Cloud AI/ML you will lead the design and delivery of Google Cloud AI and machine learning solutions within our Data & Analytics Engineering practice. As a Manager you will lead teams, coach junior professionals, manage client accounts, and drive assigned workstreams with autonomous judgment while balancing quality, timelines, and changing client needs. In this role at PwC, you will guide technical delivery across cloud-native development and testing efforts, support solution design from concept through implementation, and bring together data, analytics, and AI capabilities to address complex business needs.
Responsibilities
- Leading Google Cloud AI and machine learning engineering workstreams from planning through delivery
- Managing technical teams that build generative AI solutions for client-facing use cases
- Guiding the design, development, and deployment of LLM based applications, agent orchestration, and retrieval augmented generation patterns
- Reviewing architecture choices, code quality, and testing approaches for Python based AI solutions and digital tooling
- Directing model evaluation, prompt engineering, guardrails, and LLMOps activities across multiple delivery tracks
- Coordinating solution development using Google Vertex AI, LangChain, LangGraph, and LLM APIs
- Coaching team members on machine learning, natural language processing, and AI fluency in applied project settings
- Identifying opportunities to improve AI delivery methods, accelerate implementation, and expand reusable solution assets
- Maintaining client relationships through clear progress updates, issue resolution, and active management of expectations
What You Must Have
- At least a Bachelor's degree
- At least 5 years of experience
What Sets You Apart
- Leading Google Cloud AI/ML engineering teams and client workstreams
- Managing Generative AI, LLMOps, and model evaluation initiatives
- Building with Google Vertex AI, LangChain, and LangGraph
- Applying Python, machine learning, and NLP in delivery
- Coaching teams through agent orchestration and prompt engineering
- Driving retrieval-augmented generation, guardrails, and vector databases
The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
Learn more about how we work: https://pwc.to/how-we-work
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
As a Engineering Manager, Google Cloud AI/ML you will lead the design and delivery of Google Cloud AI and machine learning solutions within our Data & Analytics Engineering practice. As a Manager you will lead teams, coach junior professionals, manage client accounts, and drive assigned workstreams with autonomous judgment while balancing quality, timelines, and changing client needs. In this role at PwC, you will guide technical delivery across cloud-native development and testing efforts, support solution design from concept through implementation, and bring together data, analytics, and AI capabilities to address complex business needs.
Responsibilities
- Leading Google Cloud AI and machine learning engineering workstreams from planning through delivery
- Managing technical teams that build generative AI solutions for client-facing use cases
- Guiding the design, development, and deployment of LLM based applications, agent orchestration, and retrieval augmented generation patterns
- Reviewing architecture choices, code quality, and testing approaches for Python based AI solutions and digital tooling
- Directing model evaluation, prompt engineering, guardrails, and LLMOps activities across multiple delivery tracks
- Coordinating solution development using Google Vertex AI, LangChain, LangGraph, and LLM APIs
- Coaching team members on machine learning, natural language processing, and AI fluency in applied project settings
- Identifying opportunities to improve AI delivery methods, accelerate implementation, and expand reusable solution assets
- Maintaining client relationships through clear progress updates, issue resolution, and active management of expectations
What You Must Have
- At least a Bachelor's degree
- At least 5 years of experience
What Sets You Apart
- Leading Google Cloud AI/ML engineering teams and client workstreams
- Managing Generative AI, LLMOps, and model evaluation initiatives
- Building with Google Vertex AI, LangChain, and LangGraph
- Applying Python, machine learning, and NLP in delivery
- Coaching teams through agent orchestration and prompt engineering
- Driving retrieval-augmented generation, guardrails, and vector databases
The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
Learn more about how we work: https://pwc.to/how-we-work
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
PwC San Francisco, California, USA Office
405 Howard Street Suite 600, San Francisco, CA, United States, 94105
PwC San Jose, California, USA Office
488 Amaden Boulevard, San Jose, CA, United States, 95110
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What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
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- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
