Lead Software Engineer - Cloud DevOps & AI

As a Lead Software Engineer at JPMorgan Chase within the Consumer Community Banking organization, we have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

Job Responsibilities:

• Design and implement CI/CD pipelines, infrastructure-as-code (IaC) frameworks, and container orchestration strategies leveraging tools such as Kubernetes, Docker, Terraform, and Spinnaker, while utilizing AI-driven automation to streamline deployment and management across cloud and on-premises environments.
• Lead the architecture, deployment, and management of cloud infrastructure in AWS, establishing and enforcing best practices for reliability, scalability, security, and cost optimization across all cloud environments.
• Drive the adoption of AI and machine learning capabilities within DevOps workflows, including intelligent monitoring, predictive analytics, and automated remediation, while evaluating and integrating AI-powered tools to continuously improve development velocity, system reliability, and operational efficiency.
• Lead the integration of intelligent agents for workflow automation, decision-making, and process optimization.
• Develop AI-powered observability solutions to monitor, analyze, and proactively manage application and infrastructure health, automating alerting, root cause analysis, and incident response using advanced ML techniques.
• Work closely with cross-functional teams including engineering, product, and operations to identify automation opportunities and deliver impactful solutions.
• Stay abreast of emerging AI/ML technologies, frameworks, and industry trends, driving continuous improvement by evaluating and implementing new tools, methodologies, and approaches.
• Provide hands-on technical guidance to a team of software and DevOps engineers, fostering a culture of innovation, accountability, and continuous learning.
• Conduct code reviews, architectural assessments, and design discussions to uphold engineering excellence.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years in AI/ML engineering, with proven expertise in agent-based systems and automation.
• Strong experience in automating IAC development (e.g., Terraform, Ansible, CloudFormation) using AI/ML.
• Deep understanding of observability tools (e.g., Prometheus, Grafana, ELK stack) and automation using AI/ML.
• Proficiency in Python, Java, or similar programming languages; experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Excellent problem-solving, communication, and collaboration skills.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

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