Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorgan Chase within the CTO – Identity & Access Management (IAM) organization, you serve as a seasoned member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You will build and operate an AWS-based data platform and control plane that automates provisioning of cloud infrastructure, platform configuration, and data pipeline enablement (including our Databricks-on-AWS implementation). You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. We’re looking for a curious engineer who thrives in ambiguity, learns quickly, and delivers high-quality outcomes—leveraging enterprise-authorized AI tools responsibly to improve productivity and drive business value Job responsibilities • Execute software solutions across design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. • Create secure and high-quality production code and maintain services/automation that support data platform provisioning and pipeline enablement on AWS. • Design, develop, and troubleshoot software solutions for a Python-based control plane that automates platform provisioning, configuration, and pipeline enablement (including Databricks-on-AWS). • Build secure, reliable backend services and APIs that enable self-service workflows (e.g., onboarding, workspace/environment provisioning, policy/guardrails, job orchestration hooks, environment configuration, secrets/access patterns). • Implement infrastructure-as-code and automation for AWS platform components (identity controls, encryption, networking integrations, logging/monitoring, guardrails). • Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contribute learnings and reusable patterns to improve broader team effectiveness. • Apply 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. • Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development (security, resiliency, scalability, cost). • Drive reliability and observability practices (logs/metrics/tracing, retries, idempotency, timeouts, 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. • Proactively identify hidden problems and patterns in operational data and use these insights to drive improvements to coding hygiene and system architecture. Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 3+ years 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 with Python (preferred) or another modern programming language and UI technologies. • Strong experience with AWS and infrastructure fundamentals, including services such as IAM, KMS, S3, CloudWatch (and compute/orchestration such as EKS/ECS/Lambda where applicable). • Hands-on experience with infrastructure-as-code (Terraform preferred; CloudFormation acceptable) 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 within the work environment with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. • Overall knowledge of the Software Development Life Cycle. • Solid understanding of agile methodologies such as CI/CD, application resiliency, and security. Preferred qualifications, capabilities, and skills • Hands-on experience with Databricks on AWS or similar data engineering / analytics platforms (e.g., Spark-based environments, data lake/lakehouse platforms) and ecosystem components (jobs/orchestration, cluster/runtime concepts, governance/catalog concepts). • Familiarity with modern front-end technologies such as React , TypeScript , HTML/CSS. • Familiarity with data pipeline and working with large-scale datasets. • Experience with streaming or distributed systems (e.g., Apache Kafka) in production environments (good to have). • IAM domain knowledge (Auth, authorization patterns, RBAC/ABAC concepts). • Experience with observability tooling (Datadog, Splunk, Dynatrace, Grafana). • Kubernetes/Docker familiarity. Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

Requirements

Must-haves

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
We’re looking for a curious engineer who thrives in ambiguity, learns quickly, and delivers high-quality outcomes—leveraging enterprise-authorized AI tools responsibly to improve productivity and drive business value
Execute software solutions across design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
Create secure and high-quality production code and maintain services/automation that support data platform provisioning and pipeline enablement on AWS.
Design, develop, and troubleshoot software solutions for a Python-based control plane that automates platform provisioning, configuration, and pipeline enablement (including Databricks-on-AWS).
Implement infrastructure-as-code and automation for AWS platform components (identity controls, encryption, networking integrations, logging/monitoring, guardrails).
Apply 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.
Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development (security, resiliency, scalability, cost).
Drive reliability and observability practices (logs/metrics/tracing, retries, idempotency, timeouts, 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.
Proactively identify hidden problems and patterns in operational data and use these insights to drive improvements to coding hygiene and system architecture.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 3+ years applied experience
Hands-on practical experience in system design, application development, testing, and operational stability.
Strong experience with AWS and infrastructure fundamentals, including services such as IAM, KMS, S3, CloudWatch (and compute/orchestration such as EKS/ECS/Lambda where applicable).
Solid understanding of the SDLC, including CI/CD , automated testing, and safe deployment practices.
Overall knowledge of the Software Development Life Cycle.
Solid understanding of agile methodologies such as CI/CD, application resiliency, and security.
Familiarity with modern front-end technologies such as React , TypeScript , HTML/CSS.
Familiarity with data pipeline and working with large-scale datasets.
Experience with streaming or distributed systems (e.g., Apache Kafka) in production environments (good to have).

Nice-to-haves

Strong experience developing, debugging, and maintaining production code in a large corporate environment with Python (preferred) or another modern programming language and UI technologies.
Hands-on experience with infrastructure-as-code (Terraform preferred; CloudFormation acceptable) and automation-first engineering.
Preferred qualifications, capabilities, and skills

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

agileawsaipythonci/cdreacttypescriptkubernetesdocker

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Vision