Senior Software Engineer - Java, AWS & AI

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 61,000 - 101,000; Full time

Benefits offered by this job

Health insurance

On-site health centers

Retirement savings plan

Tuition reimbursement

Mental health support

Financial coaching

Diversity & inclusion

Job summary

JPMorgan Chase & Co. in Jersey City, NJ, is seeking an accomplished software engineer to design, develop, and maintain production-grade Python services and APIs that power enterprise-scale machine learning platforms.

You will architect high-throughput distributed systems in AWS, build cloud-native applications with EKS, ECS, MSK, SQS, and S3, and lead secure, observable deployments with Terraform, CloudFormation, Datadog, Dynatrace, and Splunk.

Qualifications

• Formal training in software engineering concepts required.
• 5+ years of applied software experience required.
• Advanced Python skills with OO design and modular architecture.
• Experience building large-scale cloud-native services in AWS.
• Hands-on AWS with EKS, ECS, MSK, SQS and S3.
• IaC experience with Terraform and/or CloudFormation.
• Expertise in distributed systems design and production readiness.
• Experience with observability tools (Datadog, Dynatrace, Splunk).
• Strong API design, microservices, and scalable patterns.
• CI/CD and automated deployment practices.
• Familiarity with AI-assisted development tools for coding and testing.
• Understanding of responsible AI, security, and compliance.
• Preferred: resilience patterns and event-driven architectures.

Responsibilities

• Design, develop, and maintain production-grade Python services and APIs for enterprise-scale ML platforms.
• Architect and deliver high-throughput, low-latency distributed systems in AWS.
• Build and manage scalable cloud-native apps using AWS services (EKS, ECS, MSK, SQS, S3).
• Develop reusable service frameworks and libraries to speed engineering delivery.
• Implement IaC with Terraform and CloudFormation for repeatable deployments.
• Create monitoring and observability with Datadog, Dynatrace, Splunk.
• Deploy and support applications in production meeting SLAs.
• Apply secure-by-design practices and automated testing with blue/green/canary strategies.
• Review code, provide architectural direction, and mentor engineers.
• Collaborate with product managers and SREs to deliver scalable solutions.
• Drive enterprise adoption of AI-assisted engineering practices.

Skills

Formal training in software eng.

5+ years of software experience

Advanced Python

AWS cloud-native services

EKS, ECS, MSK, SQS, S3

Infrastructure as code (Terraform, CF)

Distributed systems design

Observability tools (Datadog, Dynatrce

API design & microservices

CI/CD & deployment automation

AI-assisted coding tools

Responsible AI & security/compliance

Kafka-based messaging

Education

Software engineering certification

Bachelor’s degree in a relevant field

Tools

AWS EKS

AWS ECS

AWS MSK

AWS SQS

AWS S3

Terraform

CloudFormation

Datadog

Dynatrace

Splunk

Kubernetes

CI/CD tooling

Job description

Salary: $61,000 - 101,000 per year

Requirements:

• We require formal training or certification in software engineering concepts, along with 5+ years of applied experience.
• We need advanced Python skills, including object-oriented design and modular software architecture.
• We look for experience building and running large-scale, high-performance cloud-native services in AWS environments.
• We require hands-on experience with AWS technologies such as EKS, ECS, MSK (Kafka), SQS, and S3.
• We need strong experience implementing infrastructure as code with Terraform and/or CloudFormation.
• We require expertise in designing, deploying, and supporting distributed systems in production.
• We look for experience with observability, monitoring, logging, and alerting tools such as Datadog, Dynatrace, and Splunk.
• We need a strong understanding of API design, microservices architecture, and scalable system design patterns.
• We require experience with automated testing, CI/CD pipelines, deployment automation, and secure software engineering practices.
• We look for demonstrated use of approved AI-assisted development tools for coding, code review, testing acceleration, troubleshooting, and operational support.
• We need a strong understanding of responsible AI usage, application security, resiliency requirements, compliance standards, and mentoring engineers on best practices.
• Preferred: strong knowledge of distributed systems reliability patterns, including resiliency engineering, self-healing architectures, backpressure management, and idempotency.
• Preferred: experience optimizing real-time and event-driven architectures at scale, particularly with Kafka-based messaging systems.
• Preferred: experience implementing end-to-end observability, automated operational runbooks, and proactive monitoring frameworks.
• Preferred: familiarity with CI/CD best practices, canary deployments, blue/green release strategies, and automation within cloud environments.
• Preferred: familiarity with Generative AI and Large Language Model technologies, including building engineering solutions that leverage AI/LLM platforms.

Responsibilities:

• We design, develop, and maintain production-grade Python services and APIs that support high-impact machine learning platforms at enterprise scale.
• We architect and deliver high-throughput, low-latency distributed systems in AWS environments to support critical business workloads.
• We build and manage scalable cloud-native applications using AWS services including EKS, ECS, MSK, SQS, and S3.
• We develop reusable service frameworks, shared libraries, and modular application components that speed up engineering delivery across teams.
• We design and implement infrastructure-as-code solutions with Terraform and CloudFormation for repeatable, auditable, and scalable deployments.
• We create and maintain monitoring, alerting, and observability solutions using platforms such as Datadog, Dynatrace, and Splunk.
• We deploy and support applications in production while meeting service-level objectives and service-level agreements.
• We implement secure-by-design engineering practices, automated testing, and deployment strategies such as blue/green and canary releases.
• We review code, provide architectural direction, and mentor engineers on software engineering best practices.
• We collaborate with product managers, platform engineering teams, and site reliability engineers to deliver scalable, business-aligned solutions.
• We drive adoption of enterprise-approved AI-assisted engineering practices to improve code quality, troubleshooting, operational excellence, and delivery efficiency.

Technologies:

• AI
• API
• AWS
• Architect
• CI/CD
• Cloud
• Datadog
• Dynatrace
• Support
• Kafka
• LLM
• Machine Learning
• Marketing
• Python
• Security
• Splunk
• Terraform
• microservices
• Java
• Kubernetes
• Web

More:

We are JPMorganChase, collaborating with hackajob to connect with exceptional professionals for this role. You will join our Machine Learning Center of Excellence within the Corporate Sector, working at the intersection of cutting-edge engineering and real-world impact at global scale. Our team partners with a multi-disciplinary community of experts focused on machine learning, including deep learning and reinforcement learning. We offer a competitive total rewards package, with base salary determined by role, experience, skill set, and location, plus potential commission-based pay and/or discretionary incentive compensation for eligible roles. Our benefits may include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more. We are committed to diversity and inclusion and provide reasonable accommodations where needed. Our Corporate Functions teams support finance, risk, human resources, marketing, and other essential areas that help our business, clients, customers, and employees succeed.

last updated 40 week of 2026