Description
As a Senior Engineer - AI Platform at Target, you will be a senior individual contributor responsible for designing and building production-grade AI capabilities and helping shape the technical direction of the platform.
You will work hands-on across LLM applications, RAG, AI agents, MCP, Java/Kotlin and distributed systems, translating emerging AI capabilities into reliable software that can operate at scale.
The role is a combination of strong software engineering and practical AI engineering. You will be expected to make sound architectural decisions, solve complex technical problems, contribute to engineering standards, and mentor other engineers.
Key responsibilities include:
- Building and integrating production-grade applications using large language models
- Designing and implementing Retrieval-Augmented Generation solutions
- Building agentic workflows using agent frameworks and tool-enabled architectures
- Designing reliable patterns for agent, tool, and service interactions
- Building approaches to evaluate AI systems for correctness, reliability, and regression
Requirements:
- 4-year degree in Computer Science, Engineering, or equivalent practical experience
- 4–7 years of software engineering experience, with meaningful experience as a senior individual contributor
- Hands-on experience building and shipping LLM-powered or agentic applications into production
- Strong experience with LLM integration, prompt engineering, and production AI application patterns
- Practical experience building RAG systems, including retrieval, embeddings, and evaluation
- Experience with AI agent frameworks, tool calling, and agent orchestration
- Strong proficiency in Java/Kotlin and Spring Boot, with experience building APIs and distributed services
Desired qualifications:
- Experience building multi-agent systems or agent-to-agent architectures
- Experience with Model Context Protocol (MCP) or similar tool/context integration patterns
- Experience with vector databases, embedding systems, or modern retrieval infrastructure
- Experience designing AI evaluation frameworks, including deterministic evaluation and production regression testing