Machine Learning Engineer

Job Description:
Seeking an experienced AI Engineers to help build, optimize, and scale next-generation AI agents that support business functions across planning, allocation, forecasting, pricing, and operational execution. This role sits at the forefront of Gap's expanding AI initiative, where multiple AI agents are being developed and deployed to improve productivity, automate workflows, and drive better business outcomes.

The ideal candidate will have hands-on experience building and supporting Agentic AI solutions, integrating Large Language Models (LLMs), and developing scalable AI workflows in cloud environments. This position is less focused on traditional machine learning model development and more focused on the practical implementation, optimization, and operationalization of AI agents in production environments.

Hands-on experience with agent orchestration frameworks such as LangChain, LangGraph, or Google Agent Development Kit (ADK).

Engineer will be assigned business use cases and will own the design, implementation, and continuous improvement of AI-driven solutions that enhance decision-making and workflow efficiency across multiple business domains.

Top Must-Have Skills:

• Strong Python development experience
• Experience building or supporting AI Agents and Agentic Workflows
• Experience working with LLMs and Generative AI technologies
• Exposure to AI SDKs such as OpenAI, Anthropic, or similar platforms
• Experience integrating APIs into AI-driven solutions
• Google Cloud Platform cloud experience, including BigQuery and cloud-native services
• Experience working with unstructured data
• Understanding of AI agent optimization, deployment, and operational performance

Preferred Qualifications:

• Background in AI Engineering, Software Engineering, Machine Learning Engineering, or Data Engineering
• Experience deploying containerized applications using Docker
• Exposure to CI/CD processes and automation pipelines
• Experience working in multi-cloud environments (Google Cloud Platform preferred, Azure exposure helpful)
• Retail, supply chain, planning, forecasting, or allocation experience is a plus
• SQL and/or R experience

Responsibilities:

• Design, develop, and optimize AI agents that support enterprise business workflows
• Build and maintain agentic workflows that drive automation, execution, and business insights
• Integrate LLMs and AI services into production environments
• Utilize APIs and AI SDKs to enhance and extend AI agent capabilities
• Develop backend services and integrations using Python
• Support AI workloads leveraging Google Cloud Platform technologies and BigQuery
• Optimize AI agent performance, token utilization, and cost efficiency
• Partner with business stakeholders to understand and solve real-world use cases
• Build scalable and maintainable AI solutions that improve decision-making across multiple business domains
• Support deployment, monitoring, and operational excellence of AI-powered systems