Job Description
As a Senior AI Agent Engineer, you will build the next generation of agentic AI applications that power P&G's creative content generation platform. Working within the Integrated Creative Solutions (ICS) team, you will design and develop autonomous AI agents that orchestrate multi-modal large language models to generate, evaluate, and refine marketing images, videos, and creative assets at scale. This is a hands-on engineering role for someone passionate about pushing the boundaries of what AI agents can do.
Key Responsibilities:
- Build agentic AI applications using Google Agent Development Kit (ADK), Gemini Agent Platform, and Model Context Protocol (MCP) to automate creative content workflows.
- Design and implement multi-modal AI pipelines that leverage Gemini, Imagen, Veo, and other foundation models for image generation, video creation, and content adaptation.
- Develop evaluation frameworks (evals) to systematically measure AI agent performance, output quality, and reliability across creative generation tasks.
- Create and manage AI agent skills, tool integrations, and prompt configurations that extend agent capabilities within the Agent Platform ecosystem.
- Implement function calling, tool use, and structured output patterns to enable agents to interact with enterprise APIs, databases, and external services.
- Build RAG (Retrieval-Augmented Generation) pipelines and context management systems that ground agent outputs in brand guidelines, product data, and creative standards.
- Experiment with and rapidly prototype new agent architectures — multi-agent collaboration, graph-based workflows, and human-in-the-loop patterns.
- Instrument agents with structured logging and observability to enable debugging, performance analysis, and continuous improvement.
- Collaborate with senior engineers and product stakeholders to translate creative automation needs into working agent-powered solutions deployed on GCP Cloud Run.
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 can 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 offer
- P&G-sized projects and access to world leading IT partners and technologies from Day 1.
- Wide range of self-development possibilities (training and certifications paths).
- Competitive starting salary and benefits program (private health care, P&G stock, saving plans, sport cards).
- Regular salary increases and possible promotions - in line with your results and performance.
- Opportunity to change role every few years to be in the best place for you and best for P&G.
- At Procter & Gamble we embrace a hybrid work model that combines the flexibility of remote work with the collaborative benefits of in-office engagement. Employees can enjoy the option to work from home two days a week while also spending time in the office to foster teamwork and enhance communication.
Job Qualifications
- Bachelor's degree in Computer Science, AI/Machine Learning, Software Engineering, or a related field.
- Demonstrated hands-on experience building AI agents or agentic applications (academic projects, hackathons, personal projects, or internships count).
- Practical knowledge of designing AI Systems and frameworks.
- Experience in implementing multi-agent systems (Multi-Agent Systems) using LangChain, LangGraph, ask, CrewAI or related tools.
- Practical experience working with large language model APIs (Gemini, OpenAI, Anthropic, or equivalent) including prompt engineering, function calling, and tool use.
- Familiarity with multi-modal AI — experience generating or processing images, video, or audio using foundation models.
- Proficiency in Python with experience building applications (not just notebooks/scripts).
- Understanding of evaluation methodologies for AI systems — how to measure quality, accuracy, and reliability of generative outputs.
- Familiarity with cloud platforms (GCP preferred) and containerized deployments (Docker).
- Strong curiosity and self-directed learning ability — comfortable navigating rapidly evolving AI tooling and frameworks.
- Ability to communicate technical concepts clearly and collaborate effectively in a product-driven team.
