Engineer - Data Platform (Agentic Data Layer)

The Agentic Analytics team is building the next generation of AI-enabled analytics and data access at Target. Our work goes beyond traditional GenAI and natural-language querying. We are building an enterprise agentic analytics layer that connects people and agents to trusted analytical data, governed business metrics, contextual insights, and analytical workflows.

As an Engineer on this team, you will help design and build the software and platform capabilities behind Agent Fetch and the broader agentic data platform. You will work across agent orchestration, data and metadata access, semantic models, evaluation, observability, security, and the services that allow both users and other agents to safely interact with enterprise analytical data.

This is a highly collaborative engineering role on a team working in a rapidly evolving technical space. You will be expected to learn unfamiliar domains quickly, work independently when appropriate, pair with others when useful, and iterate as both the technology and our product strategy evolve.

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

• BS or MS in Computer Science, Information Technology, Machine Learning, Artificial Intelligence, Applied Mathematics, Physics or a relevant industry experience
• Experience designing, developing, testing and supporting software applications or platform services
• Demonstrated proficiency programming in Python or Java with the ability to become productive in additional languages and frameworks
• Experience with AI agents, LLM applications, planning, or multi-step agent workflows
• Experience with Agent orchestration frameworks such as LangGraph
• Experience in evaluation and observability for LLM- or agent-based systems
• Exposure to retrieval, context management, structured tool interfaces, or MCP-based architectures
• Exposure to data platforms, analytical data systems, metadata, lineage, or data governance
• Knowledge of semantic layers, governed metrics, LookML, Power BI semantic models, dbt, or similar technologies
• Experience with distributed systems, event-driven architectures and API’s
• Knowledge of security and authorization patterns for data- or AI-enabled applications
• Experience with automated testing and an understanding of production observability, debugging, and operational reliability
• Strong problem-solving skills, including the ability to diagnose complex behavior, identify root causes, test hypotheses and iteratively improve a solution
• The ability to quickly learn unfamiliar business and technical domains through research, experimentation, and collaboration
• Strong collaboration and communication skills, including comfort pairing with other engineers and working across teams

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here (https://corporate.target.com/about) .