Sr Engineer - AI Platform Think Tank (Python, Java, Gen AI, Agentic AI)

Target•Minneapolis, MN

3d•$98,000 - $176,000•Hybrid

About The Position

This role offers the opportunity to work on high-impact AI platform capabilities at Target, helping shape how engineering teams responsibly adopt GenAI, agent-based workflows, and scalable AI-powered solutions. You will be part of a platform team focused on innovation, engineering excellence, operational stability, and practical application of emerging AI technologies. As a Sr Engineer – AI on Target’s Think Tank Platform Engineering / AI Platform team, you will help design, build, and scale modern AI-powered engineering capabilities that support Target’s broader technology ecosystem. You will own feature development end-to-end, contribute to scalable platform solutions, support production systems, and help advance the responsible use of GenAI and agent-based technologies across the platform. This role requires strong engineering fundamentals, hands-on software development experience, and the ability to partner closely with product, engineering, and business stakeholders.

Requirements

4-year degree or equivalent experience
5+ years of software development experience
Strong knowledge of software engineering principles, distributed systems, scalable application design and secure coding practices
Demonstrated programming experience with Python, Java, Kotlin, or similar object-oriented programming languages
Experience with Spring Boot/Micronaut or similar backend application frameworks
Experience with Kafka or similar messaging and data movement systems
Strong understanding of distributed systems, scalable architecture, storage, caching, and CI/CD practices
Experience building or integrating GenAI-powered applications or agent-based systems preferred
Familiarity with agent orchestration frameworks, tool usage patterns, and workflow automation
Strong understanding of responsible AI practices, including output validation, guardrails, compliance, and data security
Experience evaluating and improving prompts, tool usage, agent reliability, and AI-assisted workflows
Experience applying data standards, policies and procedures
Strong ownership mindset with the ability to align teams around priorities
Ability to clearly communicate technical and Agile concepts to product partners and cross-functional stakeholders
Maintains technical knowledge within areas of expertise
Stays current with new and evolving technologies via formal training and self-directed education

Nice To Haves

Frontend development exposure in JavaScript or TypeScript a plus

Responsibilities

Participate in Agile team ceremonies, including daily stand-ups, sprint planning, backlog refinement, and retrospectives.
Partner with product managers, engineering teams, and stakeholders to deepen domain knowledge and align technical work to business outcomes.
Own feature development end-to-end, including design, implementation, testing, deployment, and production support.
Design and implement solutions that are testable, supportable, secure, scalable, and aligned with architectural standards.
Write clean, maintainable, and secure code across multiple languages and technology paradigms.
Contribute to code reviews and design reviews to maintain engineering quality and consistency.
Support operational stability, troubleshoot issues, and resolve production problems with minimal oversight.
Participate in on-call support after onboarding and ramp-up.
Evaluate emerging technologies and contribute to research, proof-of-concept work, and platform innovation.
Leverage GenAI tools and AI-assisted development workflows to improve development speed, code quality, testing, and documentation.
Design, build, and integrate GenAI-powered applications, agent-based systems, and orchestration workflows where appropriate.
Apply strong engineering judgment to validate AI and agent outputs for correctness, reliability, security, and compliance.
Help define and evolve best practices for responsible, scalable adoption of GenAI and agent technologies across the platform.
Improve prompting strategies, tool usage patterns, workflow automation, and agent reliability.