Sr Lead Software Engineer- Cloud Infrastructure (AWS + Full-Stack)

JPMorganChase•Houston, TX

About The Position

As a Senior Lead Software Engineer at JPMorganChase in the Corporate Sector, you will be part of an agile team enhancing, building, and delivering secure, stable, scalable technology products. You will apply advanced technical capabilities and collaborate across the organization to support the firm's portfolios. The role provides technical guidance, develops and reviews production code, influences product and engineering decisions, and advances approved AI-assisted engineering practices and automation across the software development lifecycle. You will own the end-to-end architecture of a distributed, multi-tenant platform that operates consistently as cloud SaaS and in customers' isolated AWS environments. The platform includes backend APIs, data-collection and ingestion workloads, data-pipeline jobs, and a customer-facing dashboard. You will establish and uphold security- and privacy-by-design standards, including data residency, control-plane/data-plane separation, least-privilege IAM, default-deny egress, and signed and verified artifacts. You will also contribute to an inclusive team culture and the broader engineering community.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Practical experience delivering system design, application development, testing, and operational stability, including leading and mentoring technologists.
Advanced proficiency in one or more programming languages; Java, Python, and/or JavaScript/TypeScript are strongly preferred.
Experience leading effective use of enterprise-authorized AI-assisted software development tools and setting expectations for validating AI outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations; experience coaching senior engineers or leads on compliant usage patterns and controls.
Advanced proficiency in automation, continuous delivery methods, and all aspects of the software development lifecycle.
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.
Ability to solve design and functionality problems independently with little to no oversight.
Architectural-level cloud-native experience designing and operating containerized workloads on Kubernetes (EKS), packaged and released with Helm, and provisioned using infrastructure-as-code such as Terraform, Pulumi, or CloudFormation.
Deep hands-on experience with AWS services, including EKS/ECR, RDS/PostgreSQL, S3, SQS, EventBridge, IAM, IRSA, KMS, and Secrets Manager.
In-depth knowledge of the financial services industry and its IT systems.
Demonstrated proficiency in a technical discipline such as cloud, artificial intelligence, machine learning, or large-scale data engineering, with a record of setting technical direction for others.

Nice To Haves

Experience architecting and scaling data pipelines or lakehouse platforms using Databricks, Spark, and Delta Lake, and designing event-driven ingestion for high-volume, multi-tenant workloads.
Production experience with generative AI/LLM systems, such as AWS Bedrock, self-hosted models such as vLLM, or provider APIs, including cost, latency, evaluation, and data-governance trade-offs of running inference inside a customer's VPC.
Experience defining multi-tenant architecture standards, including tenant isolation, schema-per-tenant, per-tenant provisioning, and feature entitlements.
Track record delivering software into regulated, isolated, or air-gapped environments using data-residency guarantees, egress allowlisting, and control-plane/data-plane separation.

Responsibilities

Provide technical guidance and direction to the business, technical teams, contractors, and vendors.
Develop secure, high-quality production code and review and debug code written by others.
Drive decisions that influence product design, application functionality, and technical operations and processes.
Drive adoption and governance of approved AI-assisted engineering practices, with measurable validation standards for secure coding, peer review, and automated testing.
Use software development lifecycle tools, including approved AI-assisted development and automation capabilities, to improve automation at scale.
Serve as a function-wide subject matter expert in one or more areas of focus.
Advocate for firmwide frameworks, tools, and software development lifecycle practices within the engineering community.
Influence peers and project decision-makers to consider leading-edge technologies.
Own the end-to-end architecture of a distributed, multi-tenant platform spanning cloud SaaS and isolated customer AWS environments.
Establish and enforce security- and privacy-by-design standards for the platform.
Promote diversity, opportunity, inclusion, and respect within the team.