Senior Lead Engineer - Full Stack Engineer

Senior Lead Engineer - Full Stack Engineer

This range is provided by JPMorgan

Chase. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Full Stack Software Engineer at JPMorgan Chase within the Corporate Sector of the Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.

Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. You will architect, build, and optimize scalable web applications and infrastructure platforms. You’ll lead cross-functional teams, mentor junior engineers, and drive strategic technology decisions that impact firm wide systems. This role demands deep expertise in both front-end and back-end technologies, CI/CD automation, cloud-native development, and platform engineering.

We are looking for a highly skilled Software Engineer to lead the design, development, and deployment of automation and AI-driven solutions across our Tier 3 R&D data centers. This role will focus on transforming infrastructure operations into intelligent, self-healing systems using machine learning, orchestration frameworks, and cloud-native technologies.

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Lead the design and development of full-stack applications using Java, Python, Node.js, and modern front-end frameworks (React, Angular, Spring Boot)
• Architect scalable backend services and RESTful APIs with performance and resiliency in mind.
• Drive platform engineering initiatives including CI/CD pipelines, Dev Ops automation, and infrastructure-as-code using tools like Jenkins, Git Hub Actions, Terraform, and Ansible.
• Collaborate with cross-functional teams to embed AI into SDLC pipelines and operational dashboards.
• Maintain and optimize VMware environments including ESXi, vSphere, and vCenter, with automation-first principles.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Architect and implement automation workflows for provisioning, monitoring, and compliance enforcement.
• Develop AI models for capacity forecasting, anomaly detection, and simulation test classification using supervised and unsupervised techniques.
• Integrate ML models into infrastructure platforms to enable predictive alerts, dynamic workload orchestration, and real-time decision making

• Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Strong proficiency in Java, Node.js, JavaScript, HTML, CSS, and SQL/No
  
  SQL databases, Spring Boot, Hibernate, Express.js, and React/Angular.
• Experience with CI/CD pipelines, observability tools, and event-driven architectures.
• Deep understanding of Agile methodologies, SDLC, and Dev Ops practices.
• Familiarity with cloud platforms (AWS, Azure, GCP), container orchestration (Kubernetes, Docker), MLOps tools (e.g., MLflow), and cloud platforms (AWS, Azure), deploying and monitoring LLMs using RAG, vector databases, and GPT-based models.
• Knowledge of AI, risk, bias mitigation, and model governance frameworks
• Strong problem-solving skills and ability to lead technical design discussions.
• Ability to serve as a function-wide subject matter expert in one or more areas of focus and tackle design and functionality problems independently with little to no oversight
• Adds to the team culture of diversity, opportunity, inclusion, and respect

• Strong problem-solving skills and ability to lead technical design discussions
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firm wide frameworks, tools, and practices of the…