As a Lead Software Engineer at JPMorganChase within the Commercial and Investment bank Equities group, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. 

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Cloud Platform & Infrastructure as Code Design and implement AWS cloud infrastructure using Terraform and/or CloudFormation, with emphasis on reusable modules, environment promotion, and automation. Build standardized platform components (networking, IAM patterns, EKS add-ons, observability integration) that teams can adopt consistently. Drive platform improvements that reduce manual work and establish scalable operational patterns.
• Kubernetes EKS (Core Focus) Provision, upgrade, and operate EKS clusters end-to-end (cluster lifecycle, node groups, autoscaling, cluster add-ons). Implement and support Kubernetes primitives: Deployments, StatefulSets, Services, Ingress, ConfigMaps, Secrets, namespaces, RBAC, requests/limits, PDBs, HPA, VPA, taints/tolerations, affinity, anti-affinity. Troubleshoot cluster and workload issues and improve reliability through repeatable engineering patterns.
• Security, Identity, and Secrets Enforce least-privilege IAM and workload identity patterns (including IRSA for EKS). Manage secrets using cloud-native services and Kubernetes patterns, including secure access and rotation practices. Apply security best practices across cloud and Kubernetes (network segmentation, encryption, secure configuration).
• CI CD & Release Enablement Build and maintain CI CD pipelines (e.g., Jenkins/Jules or similar) to support reliable application delivery. Support release processes and collaborate with developers to improve build/deploy workflows.
• Observability & Incident Response Monitor infrastructure health using cloud-native monitoring and observability platforms (metrics, logs, alerting). Participate in incident response, including log analysis, troubleshooting, and automation for faster containment remediation. Produce and maintain runbooks and operational documentation.
• QA Performance Testing Partner with application teams to perform end-to-end testing aligned to business requirements. Execute stress performance testing in lower environments and help establish capacity expectations and scaling approaches.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review, refactoring, test strategy acceleration, incident, root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience 
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)- AWS, Azure, or GCP

• Strong experience with Kubernetes, ideally EKS in production. Proficiency with Infrastructure as Code (Terraform and, or CloudFormation).

• Strong networking fundamentals: VPCs, VNets, subnets, routing, load balancers, security groups NSGs.

• Scripting skills in Python, Bash, PowerShell, and, or Go.

• Experience with Docker and containerized workloads.

• Solid understanding of IAM, encryption, secrets, and cloud security best practices.

• 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
• Proficient in all aspects of the Software Development Life Cycle

Preferred qualifications, capabilities, and skills

• AWS is highly preferred
• Multi-cloud experience.
• Background in security engineering or DevSecOps.
• Exposure to kdb+/q environments (helpful but not required) and ability to assist in troubleshooting/log analysis when needed.