加入 Converse 团队
Converse 致力于寻找敢于突破边界、激发潜能并持续引领我们追求伟大的运动员。我们忠于自我,坚定逐梦,将创新和灵感带给世界上的每一位运动员*。我们致力于寻找敢于突破边界、激发潜能并持续引领我们追求伟大的运动员。新一代潮流引领者、赛场指挥官、冒险家、团队凝聚者,准备好上场了吗?
WHO YOU’LL WORK WITH
This role typically reports to Sr Manager S/w Engineering within Global Converse Technology (ITC), within the Supply chain, Planning and Corporate Functions
Product Managers and Business Partners across Supply Chain, Planning, Finance, and Corporate functions
Software Engineers and Integration Engineers
Platform, DevOps, and Site Reliability Engineering (SRE) teams
Data Engineering, Analytics, Architecture, and Security teams
External technology vendors and system integrators
WHO WE ARE LOOKING FOR
We are seeking a Lead Software Engineer – Full Stack Agentic AI - for Global Converse within the ITC, within the Supply chain, Planning and Corporate Functions. You will build reliable, secure, and scalable systems— partnering across product, design, and platform teams to deliver meaningful consumer and enterprise experiences. This is a hybrid role that combines hands‑on software engineering with quality engineering and testing responsibilities.
You will contribute to building, testing, and delivering enterprise solutions that support Supply Chain, Planning, and Corporate Functions, with the flexibility to take on engineering or QA work as needed. The ideal candidate has strong coding fundamentals, understands end‑to‑end delivery, and brings a quality‑first mindset to everything they build.
Details on qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related field.
Will accept any suitable combination of education, experience, and training.
10+ years of experience in a Software Engineering role supporting enterprise systems.
Strong coding skills in one or more of the following: Java, JavaScript/TypeScript, Python, or similar languages.
Solid understanding of software delivery lifecycle, including requirements, development, testing, release, and production support.
Experience testing and/or building integrations and data flows using APIs, messaging, and batch processing.
Working knowledge of CI/CD pipelines and how to integrate automated tests into build and deployment workflows.
Experience validating data accuracy and integrity, with working knowledge of SQL and data reconciliation techniques.
Exposure to Supply Chain, Planning, ERP, or Finance systems (order management, inventory, planning, financial posting) is highly preferred.
Familiarity with cloud environments (AWS and/or Azure).
Strong communication skills and the ability to collaborate effectively across engineering and business teams.
A flexible mindset, comfortable switching between engineering delivery and QA ownership based on team needs.
Exposure to AI assisted development or testing tools—or a strong interest in learning and applying AI to improve engineering productivity and quality
Experience with AI/ML technologies or a strong interest and demonstrated eagerness to learn and apply AI driven solutions to improve software design, development, and operational efficiency.
Strong collaboration, communication, and growth mindset.
Strong understanding of Full Stack Proficiency: Strong skills in Python, TypeScript, or JavaScript, API integration, data connectors, SQL/No-SQL databases etc
AI/LLM Experience: Proven experience with Large Language Models (LLMs) and building AI agents.
Experience with RESTful APIs and database management (Dataverse or SQL).
Problem-Solving: Ability to debug agent behaviors, handle hallucinations, and optimize prompt engineering.
Knowledge of AWS/Azure OpenAI Service.
WHAT YOU’LL WORK ON
AI Agent Development/orchestration: Design, build, and implement AI agents and copilots using frameworks such as RAG
Explore and integrate AI-driven automation tools to enhance process efficiency and decision-making
Coordinate with cross-functional teams to ensure seamless integration and delivery.
Document processes, best practices, and maintain compliance with organizational standards.
Backend & Frontend Development: Create secure, high-quality, full-stack applications (React, Angular, or Vue.js for frontend?; Python/Node.js for backend?) that interact with AI models via RESTful or GraphQL APIs.
Deployment & Optimization: Deploy, monitor, and optimize AI-driven applications using containerization (Docker, Kubernetes) and cloud services (Azure).
Agentic Workflows: Implement Retrieval Augmented Generation (RAG) systems to enhance agent knowledge and accuracy.
Contribute hands on engineering work, including building and enhancing services, integrations, and automation supporting enterprise platforms.
Test and validate end to end business workflows across Supply Chain, Planning, Finance, and Corporate systems.
Validate integrations and data flows between systems such as ERP, OMS, WMS, Planning tools, and Finance platforms (REST APIs, events, batch jobs).
Participate in feature delivery, production validation, and post deployment support as needed.
Identify, document, and track defects; collaborate with engineering teams on root cause analysis and resolution.
Support release planning and execution, including smoke testing, sanity checks, and rollback validation.
Contribute to architecture evolution, security by design, and cost efficient solutions.
Mentor engineers through pairing, feedback, and knowledge sharing.
我们的招聘策略
01 申请
我们的团队拥有多元化的技能组合、知识库、意见、想法和背景。 希望你能找到适合自己的职位,因此请查看职位描述、部门和团队,找到适合你的职位。
02 与招聘人员会面或进行评估
如果被选中担任公司职位,招聘人员将会联系你开启面试流程,并在整个过程中担任你的主要联系人。 如果是零售职位,你需要完成互动式评估,包括聊天和测验,用时约 10 到 20 分钟。 无论担任什么职位,我们都希望充分了解你。因此,请尽情展现你如何提供世界一流的服务以及你的独特之处。
03 面试
从容开启这一阶段,做好充分调查,了解候选人标准并根据个人情况和背景准备可能会被问到的问题。