Lead Engineer - GenAI
Listed on 2026-05-16
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Software Development
AI Engineer
The pay range is $ - $
Pay is based on several factors which vary based on position. These include labor markets and, in some instances, may include education, work experience and certifications.
In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves.
Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays and paid vacation. Find competitive benefits from financial and education to well‑being and beyond at
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.
- 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 ope rationalise 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.
- 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 Postgre
SQL, Elasticsearch, Open/Elastic Search, Object Storage (S3/etc.) - Hands‑on experience with modern LLM ecosystems (OpenAI, Anthropic, Llama, Gemini, etc.) and product ionising GenAI capabilities
- Strong knowledge of emerging GenAI patterns, frameworks and use‑cases, including Lang Graph, Lang Chain, Google GenAI, RAG and 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.
- Experience with planning algorithms (ReAct, Tree‑of‑Thought, HTN), policy learning, reward modelling and agent performance optimisation strategies
This position will operate as a Hybrid/Flex for Your Day work…
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