Senior AI Engineer — AI Systems & Backend Lead

Roundel; Brooklyn Park (MN); Hybrid; USD 98,000 - 176,000; Full time

Benefits offered by this job

Health benefits

401(k)

Employee discount

Paid time off

Job summary

Target is seeking a Senior AI Engineer to join the Circle Card (AFCC) team in a hybrid work model. You will design and deploy AI-powered customer experiences, build scalable services, and lead architectural decisions while collaborating across engineering disciplines.

Leverage Kotlin, Java, and Micronaut to deliver production-ready AI applications, optimize latency and cost, and ensure robust observability and governance. Prior experience with LLMs and RAG is highly valued.

Qualifications

• 4 years of degree or equivalent practical experience.
• 5+ years of software engineering experience building enterprise-scale applications and backend systems.
• Hands-on experience designing and deploying production AI applications.
• Experience building autonomous or multi-agent workflows with orchestration frameworks.
• Proficiency in Python for AI development and tooling.
• Strong understanding of AI architecture, prompt engineering, and RAG concepts.

Responsibilities

• Design, develop, and maintain scalable AI-ready services using Kotlin, Java, and Micronaut.
• Build secure RESTful APIs and event-driven services for high-volume workloads.
• Lead architecture discussions, code reviews, and implementation planning.
• Collaborate with teams to integrate AI capabilities into products and platforms.
• Implement observability, governance, and security practices in AI projects.
• Explore and prototype new AI technologies and workflows.

Skills

AI engineering

Python

LangChain

MCP

Semantic Kernel

Tool calling

Retrieval-Augmented Generation

Kotlin

Java

Micronaut

PostgreSQL

Kafka

OpenTelemetry

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Docker

Spring Boot

Job description

Target is seeking a Senior AI Engineer to join the Circle Card (AFCC) team in a hybrid work model. You will design and deploy AI-powered customer experiences, build scalable services, and lead architectural decisions while collaborating across engineering disciplines.

Leverage Kotlin, Java, and Micronaut to deliver production-ready AI applications, optimize latency and cost, and ensure robust observability and governance. Prior experience with LLMs and RAG is highly valued.