Software Engineer III - AI & IoT

About the role

Join JPMorgan Chase’s technology team as a Software Engineer III focused on AI and IoT. You will design and deliver cloud‑native, full‑stack applications that combine large language model capabilities with connected device data to improve workplace experiences and operational efficiency.

Key responsibilities

• Design, develop, and troubleshoot secure, high‑quality production code for core services and algorithms.
• Create architecture and design artifacts for complex, full‑stack applications.
• Build end‑to‑end features spanning backend services and user interfaces that deliver business value.
• Integrate and operationalize LLM/generative AI capabilities such as summarization, copilots, and retrieval‑augmented generation.
• Develop IoT integrations, including telemetry ingestion, event processing, device health monitoring, and smart‑building workflows.
• Analyze large, diverse datasets, generate visualizations, and synthesize insights for reporting.
• Identify hidden problems in data, logs, and system behavior to drive continuous improvement.
• Participate in engineering communities of practice and share knowledge of emerging technologies.

Required profile

• Formal training or certification in software engineering concepts with at least 3 years of applied experience.
• Strong system design, application development, and operational stability skills.
• Advanced proficiency in Java; working knowledge of Python is a plus.
• Hands‑on experience productizing Large Language Models and generative AI.
• Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, scikit‑learn, and Hugging Face.
• Experience with distributed systems and cloud platforms (AWS, GCP, or Azure).
• Expertise in microservices, RESTful APIs, and relational or NoSQL databases.
• Knowledge of Docker, Kubernetes, Helm, and CI/CD tooling.
• Deep understanding of IoT architectures, protocols, device management patterns, and security best practices.

Required skills

• Java
• Python
• Large Language Models (LLMs)
• Generative AI
• PyTorch
• TensorFlow
• scikit‑learn
• Hugging Face
• AWS
• GCP
• Azure
• Microservices
• RESTful APIs
• Relational databases
• NoSQL databases
• Docker
• Kubernetes
• Helm
• CI/CD
• IoT architectures
• Telemetry ingestion
• Event processing