Senior Manager, Google AI & Data Solutions Architect

PWC

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Work type
On-site
Location
Dallas, TXRaleigh, NCCharlotte, NCChicago, ILCincinnati, OHCleveland, OHColumbia, SCColumbus, OHBaltimore, MDRichmond, VARochester, NYRosemont, ILSacramento, CABoston, MASt. Louis, MOSalt Lake City, UTSan Antonio, TXSan Diego, CASan Francisco, CASilicon Valley, CASeattle, WASpartanburg, SCAlbany, NYStamford, CTTampa, FLAtlanta, GAToledo, OHAustin, TXTulsa, OKWashington, DCDenver, CODes Moines, IADetroit, MIBoca Raton, FLBuffalo, NYFlorham Park, NJFort Worth, TXGreensboro, NCHartford, CTHouston, TXGrand Rapids, MIIndianapolis, INIrvine, CAJacksonville, FLKansas City, MOLas Vegas, NVLittle Rock, ARLos Angeles, CALouisville, KYBirmingham, ALFayetteville, ARMelville, NYMiami, FLMilwaukee, WIMinneapolis, MNMontpelier, VTNashville, TNNew Orleans, LANew York, NYOklahoma City, OKOrlando, FLPhiladelphia, PAPhoenix, AZPittsburgh, PAPortland, OR
Salary
$124,000–$280,000 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

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Competitive pay

How this pay compares to similar roles

Similar $198k
This role $202k
$105k most similar roles pay here $299k

This role pays more than 51% of similar roles. Most pay $160,812–$235,750 — the shaded band above. At the midpoint, this role pays about $202k versus about $198k for comparable roles.

Based on 240 similar postings.

Employer

About PWC

PwC (PricewaterhouseCoopers) is one of the "Big Four" accounting and professional services firms, providing audit, tax, and advisory services to companies, governments, and institutions worldwide. Industry: Professional Services & Accounting

PWC currently has 104 open roles on FindRole.

Listed pay typically runs $99,000–$232,000 across 101 roles with salary data.

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At a glance

TL;DR · Senior Manager, Google AI & Data Solutions Architect

As a Google AI & Data Solutions Architect, Senior Manager within the Data and Analytics Engineering practice, you will lead client-focused solution design for generative AI and data modernization initiatives. You will be responsible for translating business needs into technical blueprints, guiding teams through prompt engineering, context engineering, and agent orchestration to build scalable applications. Your daily work involves developing LLM evaluation methods, guardrails, and LMMOps practices while shaping data modernization strategies across cloud platforms and vector databases. To succeed, you must utilize Python, machine learning, natural language processing, LangChain, LangGraph, and Vertex AI. You will solve complex problems regarding reliable AI deployment and scalable use cases by coordinating rapid experimentation cycles to validate solution fit and presenting technical trade-offs to stakeholders to support modern data platform integration and adoption planning.

What you'll do

  • Design client-focused solution architectures for generative AI and data modernization initiatives.
  • Translate business requirements into technical blueprints using Google Vertex AI, LLM APIs, and RAG.
  • Guide teams through prompt engineering, context engineering, and agent orchestration for scalable applications.
  • Develop LLM evaluation methods, guardrails, and LLMOps practices to ensure reliable deployment.
  • Create data modernization strategies involving cloud platforms, vector databases, and digital tooling.
  • Prototype and refine AI-enabled solutions using Python, machine learning, and natural language processing.
  • Present technical options, trade-offs, and implementation plans to client leaders and internal teams.
  • Coordinate rapid experimentation cycles to validate solution fit and inform design choices.

What we're looking for

  • At least a Bachelor's degree.
  • At least 7 years of experience.
  • Experience leading large Google Cloud AI and data programs (preferred).
  • Experience delivering generative AI, LLM, and vector database solutions (preferred).
  • Proficiency in Python, LangChain, LangGraph, and Vertex AI (preferred).
  • Experience with LLMOps, guardrails, and evaluation methods (preferred).
  • Ability to translate technical concepts into client-ready narratives (preferred).
  • Ability to coach teams through ambiguity and complex decisions (preferred).

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