Full-stack Python and React Software Engineer III

JPMorganChase • Plano, TX

3d

About The Position

As a Software Engineer III at JPMorgan Chase within the CTO – Identity & Access Management (IAM) organization, you will serve as a seasoned member of an agile team, designing and delivering trusted, secure, stable, and scalable technology products. You will build and operate an AWS-based data platform and control plane that automates cloud infrastructure provisioning, platform configuration, and data pipeline enablement, including the Databricks-on-AWS implementation. The role delivers critical technology solutions across multiple technical areas in support of the firm’s business objectives. It calls for a curious engineer who thrives in ambiguity, learns quickly, and delivers high-quality outcomes, using enterprise-authorized AI tools responsibly to improve productivity and business value.

Requirements

• Formal training or certification in software engineering concepts and at least 3 years of applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Strong experience developing, debugging, and maintaining production code in a large corporate environment using Python or another modern programming language.
• Familiarity with modern front-end technologies such as React, TypeScript, and HTML/CSS.
• Strong experience with AWS and infrastructure fundamentals, including IAM, KMS, S3, and CloudWatch, and compute or orchestration services such as EKS, ECS, or Lambda where applicable.
• Hands-on experience with infrastructure-as-code and automation-first engineering.
• Solid understanding of the SDLC, including CI/CD, automated testing, and safe deployment practices.
• Hands-on experience using enterprise-authorized AI-assisted software development tools, with the ability to critically evaluate, validate, and refine generated outputs for correctness, performance, and security.

Nice To Haves

• Hands-on experience with Databricks on AWS or similar data engineering and analytics platforms, such as Spark-based environments or data lake/lakehouse platforms, and ecosystem components including jobs/orchestration, cluster/runtime concepts, and governance/catalog concepts.
• Experience with streaming or distributed systems, such as Apache Kafka, in production environments.
• IAM domain knowledge, including authentication, authorization patterns, and RBAC/ABAC concepts.
• Experience with observability tooling such as Datadog, Splunk, Dynatrace, or Grafana.

Responsibilities

• Execute software solutions across design, development, and technical troubleshooting, using approaches beyond routine or conventional methods to solve technical problems.
• Create secure, high-quality production code and maintain services and automation supporting AWS data platform provisioning and pipeline enablement.
• Design, develop, and troubleshoot a Python-based control plane for platform provisioning, configuration, and pipeline enablement, including Databricks on AWS.
• Build secure, reliable backend services and APIs for self-service workflows, including onboarding, workspace and environment provisioning, policies and guardrails, job orchestration hooks, environment configuration, and secrets and access patterns.
• Implement infrastructure-as-code and automation for AWS platform components, including identity controls, encryption, networking integrations, logging and monitoring, and guardrails.
• Use enterprise-authorized AI coding-assistance tools to improve code quality, delivery speed, and productivity; validate outputs through peer review, automated testing, and secure coding standards; and share reusable patterns and learnings.
• Use SDLC toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to improve the value realized by automation.
• Produce architecture and design artifacts for complex applications and ensure software development meets security, resiliency, scalability, and cost constraints.
• Drive reliability and observability practices, including logs, metrics, tracing, retries, idempotency, timeouts, and runbooks, and continuously improve platform operations.
• Partner with IAM/security, data engineering, and application teams to integrate platform controls and enable secure analytics at scale.
• Identify hidden problems and patterns in operational data and use insights to improve coding hygiene and system architecture.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed