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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Lead Software Engineer - **Company:** JPMorgan Chase & Co. - **Location:** Jersey City, NJ, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Code Review, Continuous Delivery, Continuous Integration, Software Design Patterns, Python (Programming Language), Machine Learning, Performance Tuning, Software Deployment, Enterprise Software Applications, Retrieval-Augmented Generation, Prompt Engineering, Containerization, Data Management, Software Version Control, Docker, Databricks - **Published:** September 11, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28010701/Senior-Lead-Software-Engineer-New-Jersey-Jersey-City-7463 ## About the Role * Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience * Advanced proficiency in Python with strong software engineering fundamentals, including testing, design patterns, version control, and code review practices. * Hands-on experience building, evaluating, and deploying machine learning or large language model-enabled systems into production environments. * Practical experience with prompt engineering and retrieval-augmented generation, including evaluation methods and quality measurement. * Experience designing and operating reliable services, including incident response readiness, performance tuning, and operational stability for data-intensive systems. * Demonstrated ability to lead technical decisions and deliver outcomes through ambiguity, balancing speed, risk, and long-term maintainability. * Strong communication skills with the ability to explain technical trade-offs to both technical and non-technical stakeholders. Preferred qualifications, capabilities and skills * Experience with agent orchestration frameworks (for example, LangGraph, LlamaIndex, Google ADK or custom orchestration) and evaluation tooling for large language model systems. * Experience with continuous integration and continuous delivery practices and containerization (Docker and Kubernetes) for production deployments. * Familiarity with vector databases, embedding pipelines, or graph-based memory approaches used in retrieval-augmented generation solutions. * Experience with cloud and machine learning platforms (for example, Amazon Web Services, Databricks, or comparable platforms). * Experience contributing to AI governance, validation approaches, or guardrail frameworks in enterprise settings. ## Description Help shape how teams across the firm build and deploy agentic artificial intelligence products-at scale, with quality, and with measurable impact. You will work on a high-visibility platform that accelerates engineering teams, raises delivery standards, and turns complex business needs into reliable production outcomes. Join a team where strong engineering, thoughtful collaboration, and continuous learning are core to how we operate., As a Senior Lead Software Engineer - Agent Builder Platform at JPMorganChase within Enterprise Technology, AI and Machine Learning & Data Platforms, you will lead the technical design and delivery of agentic AI products and platform capabilities used by engineering teams across the organization. You will translate high-impact business problems into production-grade solutions, from discovery and design through deployment and ongoing operations. You will set a high engineering quality bar while partnering closely with product and stakeholder groups to deliver measurable outcomes., * Lead end-to-end delivery of agentic AI and large language model-powered use cases from problem framing and technical design through production deployment and monitoring. * Own core platform services and reusable components that enable teams to build, evaluate, and operate AI agents safely at scale. * Establish engineering standards through hands-on system design, rigorous code review, and mentorship to improve reliability, maintainability, and developer experience. * Build and operationalize evaluation, testing, and observability capabilities (tracing, metrics, logs, and analytics) to continuously improve solution quality. * Implement robust safety and governance patterns, including guardrails, access controls, and audit-ready operational practices aligned to enterprise expectations. * Partner with product managers and stakeholders to shape roadmaps, define success metrics, and prioritize work that delivers measurable business impact. * Drive cross-functional alignment across engineering, data, security, and risk partners to ensure solutions are secure, stable, and scalable. * Contribute to technical documentation, reference implementations, and enablement content that accelerates adoption and responsible usage. ## Related Videos - [Java Meets AI: Empowering Spring Developers to Build Intelligent Apps](https://www.wearedevelopers.com/videos/1554-java-meets-ai-empowering-spring-developers-to-build-intelligent-apps) - [Are Code Reviews Worth It? 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