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P&G was founded over 180 years ago as a simple soap and candle company. Today, we're the world’s largest consumer goods company and home to iconic, trusted brands that make life a little bit easier in small but meaningful ways. We've spanned three centuries thanks to three simple ideas: leadership, innovation and citizenship. The insight, innovation and passion of hardworking teams have helped us grow into a global company that is governed responsibly and ethically, that is open and visible, and that supports good causes and protects the environment. This is a place where you can be proud to work and do something that matters.

Dedication from Us: You'll be at the core of breakthrough innovations, be given exciting assignments, lead initiatives, and take ownership and responsibility, in creative workspaces where new insights thrive. All the while, you'll receive outstanding training to help you become a leader in your field. It is not just about what you'll do, but how you'll feel: encouraged, valued, purposeful, challenged, heard, and inspired.

What we Offer: Continuous mentorship – you will collaborate with peers and receive both formal training as well as day-to-day mentoring from your manager dynamic and encouraging work environment– employees are at the center, we value every individual and support initiative, promoting agility and work/life balance.

The Data Architecture job family involves leading the data design for an application, solution, or business domain, helping to define how data will flow, and be stored and structured.

We are looking for an Architect to join our Supply Chain Innovation organization and lead the design of enterprise-scale Generative AI solutions that run on top of P&G's data platform. At P&G, AI is not a standalone experiment — it is an operational interface over the data that runs our business, from supply chain and vendor systems to retail distribution and consumer insights. In this role you will own the architecture for how our AI systems retrieve, reason over, and act on enterprise data, working hands-on while setting the standards other engineering teams build against. This is an exciting opportunity for a self-motivated architect who enjoys solving complex technical problems and delivering high-impact global solutions.

Key Responsibilities:

● Own end-to-end architecture for enterprise GenAI solutions — retrieval, orchestration, integration, and evaluation — ensuring they are scalable, secure, and aligned to business outcomes.

● Design production retrieval-augmented generation (RAG) architectures over enterprise data, including document ingestion and chunking, indexing strategy, hybrid lexical and semantic retrieval, re-ranking, and relevance tuning.

● Architect multi-phase agent and tool-calling workflows with deterministic guardrails — scoped tool access, structured output schemas, validation, bounded retries, explicit completion contracts, and fallback handling — so that non-deterministic models meet production reliability standards.

● Design the data ingestion and synchronization foundations that support AI grounding — streaming and change data capture from enterprise sources, canonical data models, and incremental sync that keeps indexes and downstream systems current.

● Enforce data governance and strict multi-tenant isolation boundaries across brands, regions, and partners, applying access control, PII protection, and Responsible AI principles by default.

● Establish evaluation and observability standards for AI workloads — curated test sets, automated quality scoring including model-based judging, regression suites in CI/CD, and end-to-end tracing of model behavior in production.

● Own the operational economics of AI systems: latency and throughput targets, inference and token cost management, caching strategies, and routing work to the appropriate model for the task.

● Act as the principal technical authority for AI architecture — lead design reviews, resolve complex performance and integration issues, mentor engineers, and champion Agile, DevOps, and CI/CD practices.

Ideal Candidate:

● A hands-on architect who can independently design end-to-end solutions while remaining active in development, code review, and production problem-solving.

● Treats AI systems as distributed data systems — designs for failure, latency, duplication, and drift rather than assuming the happy path.

● Collaborative and self-motivated, able to work across global teams, influence stakeholders without formal authority, and translate business needs into scalable technical solutions.

 

About us

We produce globally recognized brands, and we grow the best business leaders in the industry. With a portfolio of trusted brands as diverse as ours, it is paramount our leaders are able to lead with courage the vast array of brands, categories and functions. We serve consumers around the world with one of the strongest portfolios of trusted, quality, leadership brands, including Always®, Ariel®, Gillette®, Head & Shoulders®, Herbal Essences®, Oral-B®, Pampers®, Pantene®, Tampax® and more. Our community includes operations in approximately 70 countries worldwide.

Visit http://www.pg.com to know more.

We are an equal opportunity employer and value diversity at our company. We do not discriminate against individuals on the basis of race, color, gender, age, national origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability, HIV/AIDS status, or any other legally protected factor

Job Qualifications

Job Qualifications:

● Bachelor's degree in Computer Science, or a related technical field, or equivalent practical experience.

● 10+ years of experience in software engineering, with a significant focus on architecture and technical leadership of large-scale, multi-tenant, or high-throughput platforms.

● Hands-on experience designing and delivering production Generative AI solutions — retrieval-augmented generation, LLM-based classification and extraction, or multi-phase agent workflows — including the schema validation, guardrails, and fallback logic that make them dependable.

● Proven experience architecting orchestration layers for distributed systems — event-driven and streaming pipelines, workflow and state management, idempotency, bounded retries, and recovery from partial failure — and applying the same discipline to AI and agent workflows.

● Strong grounding in search and retrieval: inverted indexes and lexical relevance scoring, vector and semantic similarity, hybrid retrieval and rank fusion, re-ranking, and the effect of data freshness on retrieval quality.

● Experience defining quality and evaluation practices for probabilistic systems — curated test sets, regression suites, automated and model-based scoring of output quality, and production tracing.

● Experience integrating heterogeneous enterprise systems and data sources at scale across streaming, API, and file-based patterns, with strong data modeling and schema governance instincts. ● programming skills in at least one backend language (Python, Node.js/TypeScript, or similar), with hands-on experience across document and relational data stores.

● Cloud-native engineering experience (Azure) with containerization, CI/CD pipelines, monitoring, and observability as default practice.

● Ability to lead technical design discussions, drive solution decisions, and operate as a hands-on technical lead within cross-functional and global teams.

● Strong verbal, written, and interpersonal communication skills, with the ability to collaborate effectively with technical and business stakeholders.

Preferred: Working knowledge of modern lakehouse platforms (Databricks, Delta Lake, Unity Catalog) and medallion data architectures; familiarity with AI governance, guardrails, and evaluation tooling; experience integrating enterprise systems; experience designing for regulated or highly sensitive data environments.

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