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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack Engineers - **Company:** APIPHANY CORPORATION - **Location:** San Francisco, CA, United States - **Salary:** $136,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Distributed Systems, Design of User Interfaces, Human-Computer Interaction, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Machine Learning, Node.Js, Tensorflow, Requirements Management, Smart Devices, Software Deployment, Software Engineering, TypeScript, Unstructured Data, Scripting, Pytorch, ReactJS, Backend, Information Technology, ONNX (Open Neural Network Exchange) Format, Data Analytics, Data Management, Front End Software Development, Multiaccess Edge Computing, Industrial Software, Data Pipelines - **Published:** September 25, 2026 - **Apply:** https://www.careerbuilder.com/job-details/full-stack-engineers-san-francisco-ca--4d0ef602-5c64-4e69-ae33-8b46a89ddced ## About the Role Bachelor's degree in computer science, information technology, software engineering, or a related field.One year of experience as a Software Engineer or Developer or related that includes the following: 1. 0-to-1 product development in building and shipping software from conception, navigating uncertainty and scaling from Minimum Viable Product (MVP) to production. 2. Full-stack engineering, including front-end frameworks (React, TypeScript, or similar) and backend development (Python, Node.js, or similar). 3. Industrial automation, predictive maintenance, process optimization, quality control, or smart factory technologies. 4. AI/ML deployment, including integrating ML models into production applications using tools such as TensorFlow, PyTorch, or ONNX. 5. Working with industrial data, including time-series sensor data, machine telemetry, and real-time control systems. 6. Cloud and edge computing, including deploying applications on AWS, GCP, or Azure, and running AI models on edge devices. Salary:$136,000 - $160,000/year Skills: Aerospace and Defense, Artificial Intelligence (AI), Automation, Category Development, Cloud Computing, Computer Science, Control Systems, Customer/Client Research, Data Management, Distributed Computing, Information Technology Software, Large-Scale Systems, Manufacturing, Manufacturing Execution Systems (MES), Manufacturing Software, Manufacturing/Industrial Processes, Node.js, Physics, Predictive Modeling, Process Improvement, Product Development, Production Systems, Programmable Logic Controller (PLC), Prototyping, Python Programming/Scripting Language, Quality Control, React.js, Requirements Management, Software Development, Software Engineering, Supervisory Control and Data Acquisition (SCADA), Telemetry, Unstructured Data, User Interface/Experience (UI/UX) ## Description * Develop AI-powered manufacturing applications:Build full-stack solutions that integrate real-time AI (Artificial Intelligence) models for predictive maintenance, anomaly detection, defect classification, and process optimization. * Engineer for complexity and scale:Design and implement robust, distributed systems that handle large-scale data pipelines, streaming industrial sensor data, and real-time AI inference. * Integrate with factory-floor systems:Work with Industrial Internet of Thing (IIoT), Manufacturing Execution System (MES), Supervisory Control and Data Acquisition (SCADA), Programmable Logic Controls (PLCs), and edge computing to deploy AI models that interact with manufacturing processes in real time. * Bridge AI and human decision-making:Develop intuitive, high-performance interfaces that allow operators, engineers, and managers to interpret AI-driven insights and take action. * Own the full-stack:Build and optimize front-end applications (React, TypeScript, etc.) and backend services (Python, Node.js, or similar), ensuring seamless end-to-end experiences. * Ship in real-world production environments:Deploy software that runs in factories, on edge devices, or in the cloud, working within the constraints of industrial infrastructure. * Iterate quickly in a high-uncertainty domain:Prototype, test, and refine solutions based on direct user feedback and real-world performance data. ## Related Videos - [Robots are coming into the wild! 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