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Software Engineer II - Terraform, AWS, Python
JPMorganChase
linkedin
Bengaluru, Karnataka, India
2-4 years
Not Disclosed
Full time
06 May 2026
Top Skills:
AgileAiApi GatewayArchitectural DesignAuditAutomationAwsAzureCi/cdCi/cd PipelineCloudCluster ManagementComplianceContainerizationCost OptimizationDatadogDeveloper ToolDockerEc2EnterpriseGcpGovernanceKubernetesLambdaMicroservicesMulti-cloudNetworkingPerformance TuningPipelinePrometheusPythonRbacS3SamlSdlcSplunkStakeholder CommunicationState ManagementTerraformToolingTroubleshootingWealth Management

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Job Description

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II at JPMorgan Chase within the Asset & Wealth Management, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job Responsibilities

  • Develops Python services, APIs, and tooling to improve CI/CD, deployment orchestration, and developer productivity on AWS
  • Builds scalable, secure microservices and batch workflows using AWS services; ensure best practices for networking, identity, and security
  • Owns infrastructure as Code with Terraform (modules, state management, environments); establish standards, reviews, and automation for plans/apply
  • Builds integrations with enterprise systems and AWS services in Python; create reusable SDKs, CLI tools, templates, and libraries
  • Implements policy-as-code, audit logging, compliance controls; enforce RBAC and secure secrets handling across applications and infrastructure
  • Optimizes deployment strategies (canary, blue/green), rollbacks, approvals, and gates within CI/CD pipelines
  • Drives automated testing (unit, integration, contract) with Python frameworks; manage test data and continuous quality gates.

Ensures reliability and observability with logging, metrics, tracing, alerts; define SLOs and error budgets

  • Implements performance tuning and cost optimization across compute, storage, and networking
  • Collaborates with product, platform, security, and SRE teams
  • Contributes to roadmap, estimation, and delivery plans; manage technical risk, debt, and cross-team dependencies

Required Qualifications, Capabilities, And Skills

  • Formal training or certification on software engineering concepts and 2+ years applied experience
  • Proficiency in full stack development and strong experience with CI/CD platforms
  • In-depth experience designing, deploying, and managing solutions on AWS, including VPC, IAM, EC2, S3, Lambda, and networking/security best practices
  • Hands-on expertise with infrastructure-as-code using Terraform for provisioning and managing cloud resources
  • Proficient in containerization with Docker, including building, optimizing, and securing container images.

Strong background in orchestrating and scaling workloads using Kubernetes RBAC, and cluster management

  • Familiarity with multi-cloud environments (AWS, Azure, GCP) and integrating cloud-native services into CI/CD pipelines.

Expertise in pipeline design, deployment strategies, and release governance in regulated environments

  • Must have a security-first mindset, secrets management, RBAC, OIDC/SAML, compliance, audit, and policy-as-code (OPA)
  • Proficiency on observability; logs, metrics, tracing (Datadog, Splunk, Prometheus, OpenTelemetry)
  • Strong architectural design, documentation, and stakeholder communication skills

Preferred Qualifications, Capabilities, And Skills

  • Experience with Agentic AI or integrating AI/ML models into CI/CD workflows.

Familiarity with AI-driven automation, intelligent agents, or LLM-based developer tools

  • Experience with API Gateway, container orchestration, serverless architectures, and Terraform Cloud/Enterprise
  • Knowledge of security best practices in AWS, especially as they relate to AI/ML workloads.

Exposure to prompt engineering, AI workflow orchestration, or embedding AI stages in the SDLC

  • Interest in continuous learning and experimentation with emerging AI technologies in software engineering

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