GEN AI Engineer

Gen-AI Engineer

About US

Johnson Electric is one of the world's largest providers of motion solutions, supplying nearly every major brand in automotive, industrial, and consumer markets. Our Smart Factory initiative leverages advanced analytics, AI and IIoT to drive zero-defect quality, lights-out manufacturing, and sustainable operations across 30+ plants on five continents.

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.

Both roles will be cross-trained. Gen-AI specialists will learn industrial ML, and ML engineers will gain exposure to generative AI toolchains.

Gen-AI Engineer

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

1. Architecture and Strategy
2. Define Gen-AI architecture blueprints, design guidelines, and model-cards aligning with JE data privacy, OT-IT convergence and cost models.
3. Establish enterprise patterns for RAG, model fine-tuning, agentic workflows, security isolation, and cost governance.
4. Platform Delivery
5. 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.
6. 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.
7. Productionize New Use Cases
8. Partner with functional SMEs (quality, maintenance, logistics, R&D) to transform high-value ideas into production Gen-AI solutions.
9. 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.
10. Document reusable patterns and feed lessons learned back into the platform backlog to accelerate subsequent use-case onboarding.

Qualifications

• 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).