Lead Engineer - GenAI

About us:

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.

Join Merchandising Engineering, a globally distributed engineering team building the systems at the very heart of Target retail. We power Target’s core merchandising capabilities—Item, Price, Promo, Merchandising Optimization, Space Planning, Vendor Experience, and our growing Owned Brand portfolio—at massive scale. Our teams solve complex, high impact problems using cutting edge technologies, including advanced AI and machine learning, to deliver intelligent, data driven experiences to millions of guests and thousands of merchants. This is a team where engineers shape the future of retail technology, influence enterprise wide strategy, and grow their careers by working on platforms that directly define how Target curates, prices, plans, and delivers the products our guests love.

As a Lead Engineer, you serve as the technical anchor for the engineering team that supports a product. You create, own and are responsible for the application architecture that best serves the product in its functional and non-functional needs. You identify and drive architectural changes to accelerate feature development or improve the quality of service (or both). You have deep and broad engineering skills and are capable of standing up an architecture in its whole on your own, but you choose to influence a wider team by acting as a “force multiplier”.

About this Team:

Use your skills, experience and talents to be a part of groundbreaking thinking and visionary goals. As a Lead Engineer, you’ll take the lead as you…

• Design and implement autonomous AI agents capable of multi-step reasoning, task planning, tool usage, memory/state management, and iterative execution.

• Lead development of multi-agent coordination frameworks, agent orchestration layers, workflow engines, and tool invocation pipelines.

• Apply hands-on expertise with LLMs (OpenAI, Anthropic, Llama, Gemini, etc.) including prompt engineering, model adaptation, and inference optimization.

• Build and operationalize evaluation systems to measure agent accuracy, robustness, cost efficiency, latency, and reliability.

• Implement safety and trust mechanisms including content filters, alignment techniques, hallucination mitigation, monitoring pipelines, and auditability.

• Build data pipelines to support training and fine-tuning, synthetic data generation, feature stores, and real-time inference workflows.

• Use technology acumen to evaluate and adopt emerging technologies, execute research/proof-of-concepts, and establish scalable engineering patterns and best practices.

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

About you:
• 4 year degree or equivalent experience
• 7+ years of software development experience with at least one full cycle implementation
• Demonstrates strong domain-specific knowledge regarding Target’s technology capabilities, and key competitors’ products and differentiating features

• Proficiency in Java and Python

• Experience with PostgreSQL, Open/Elasticsearch, Object Storage (S3/etc.)

• Hands-on experience with modern LLM ecosystems (OpenAI, Anthropic, Llama, Gemini, etc.) and productionizing GenAI capabilities

• Strong knowledge of emerging GenAI patterns, frameworks and use-cases, including:

• LangGraph / LangChain / Google GenAI, etc.

• Context Engineering / RAG / Agentic AI

• Experience designing scalable, reliable systems with strong performance, cost, and operational health awareness

• Strong stakeholder communication and ability to lead through influence across teams and partners

• Experience building highly scalable distributed systems

• Demonstrates broad and deep expertise in multiple computer languages and frameworks (e.g., open source). Designs, develops, and approves end-to-end functionality of a product line, platform, or infrastructure

Nice to have:

• Experience with planning algorithms (ReAct, Tree-of-Thought, HTN), policy learning, reward modeling, and agent performance optimization strategies

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ location the role is assigned to (Brooklyn Park, MN or Sunnyvale, CA) and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.