Generative AI Engineer
Indexed description
You will be joining a high-impact, hands-on CoE team that owns the full analytical stack: from edge data acquisition and cloud ingestion to model deployment and smart factory adoption.
You will own the end-to-end Gen AI technology stack for Johnson Electric. Design, build and govern reusable toolchains, unlock new use-cases and establish DevOps and MLOps best practices that can scale.
Key Responsibilities
Architecture and Strategy
- Define Gen-AI architecture blueprints, design guidelines, and model-cards aligning with JE data privacy, OT-IT convergence and cost models.
- Establish enterprise patterns for RAG, model fine-tuning, agentic workflows, security isolation, and cost governance.
- Build and operate a reusable Gen-AI platform on Azure (AKS, AzureML, Azure OpenAI) provisioned via IaC (Terraform/Bicep) and managed through DevOps pipelines such as Azure DevOps.
- Integrate and orchestrate Gen-AI building blocks – commercial & open-source LLM APIs, MCP tooling, frameworks such as LangChain and LlamaIndex, vector databases, Azure AI Search indexes.
- Partner with functional SMEs (quality, maintenance, logistics, R&D) to transform high-value ideas into production Gen-AI solutions.
- Guide teams through the full GenAI application lifecycle: problem framing, data acquisition, prompt and model design, human-in-the-loop validation, deployment, monitoring, and iterative improvement.
- Document reusable patterns and feed lessons learned back into the platform backlog to accelerate subsequent use-case onboarding.
- 5+ years in Data / AI engineering, 2+ years specifically building or productizing Gen-AI / LLM solutions in production.
- Deep understanding of LangChain / LlamaIndex (RAG, Agentic workflows).
- Expert in prompt engineering, agentic concepts, memory, and tool management
- Strong coding skills in Python (FastAPI, asyncio, Pydantic) and at least one typed language (Java, C#, or Go).
- Experience in Machine Learning preferably in manufacturing / IoT / edge AI.
- Expert in Azure Cloud Services for AI or equivalent.
- Hands-on with Docker/Kubernetes, GPU containers, CUDA drivers, and performance profiling.
- Proven experience translating business value metrics into technical architecture.
- Excellent stakeholder communication; able to navigate between OT, IT, cyber-security, and business teams.
- Fluency with DevOps & IaC (Azure DevOps, Terraform / Bicep, GitHub Actions).
欢迎加入我们全球性、富包容和多元化的团队!
我们的目标是通过创新的驱动系统提高每一个产品接触者的生活质量。我们是一个真正的全球性团队,我们有着共同的价值观因而联结在一起。我们的文化是建基于每一位员工为公司带来的多样性、知识、技能、创意和才能之上。我们的员工是我们企业最宝贵的资产。我们致力于为员工提供一个包容、多元和平等的工作场所,在这里无论他们的年龄、性别、肤色、种族或宗教信仰如何,不同背景的员工都能感到受重视和尊重。我们致力于激励我们的员工成长,以主人翁精神行事,并在他们所做的工作中找到成就感和意义。
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