Software Engineer Jobs in Jersey City, NJ

Develops and maintains Salesforce CRM solutions using Apex, Lightning, LWC, APIs, integrations, and enterprise development practices. Designs secure, scalable software, troubleshoots technical issues, creates architecture artifacts, and improves data quality through reports and dashboards. Collaborates within an agile team, applies CI/CD and resiliency standards, and uses AI-assisted tools for coding, testing, documentation, and productivity while validating outputs for security and correctness.

Builds and supports a managed AWS Databricks data platform, including platform design, configuration, workspace administration, monitoring, troubleshooting, and operational stability. Develops software using Python or Java, automated testing, cloud infrastructure automation, Spark, and Terraform. Provides engineering support to data engineering, data science, machine learning, application, and SRE teams while applying secure, responsible AI-assisted development practices.

Build and enhance machine learning platform capabilities, including model and feature registries, governance tooling, data preparation, annotation workflows, lineage, and auditability. Develop cloud-native microservices and APIs for scalable model delivery, along with LLM-powered capabilities using prompts, agents, tool integration, and retrieval. Create architecture artifacts, ensure secure and resilient implementations, analyze telemetry and feedback, and improve observability, code quality, and developer experience.

Develops secure, scalable Java and Spring Boot applications within an agile technology team. Responsibilities include software design, coding, testing, troubleshooting, architecture documentation, data analysis, system stability, and continuous improvement. The role also contributes to engineering practices and uses enterprise-approved AI coding tools and automation. Required technologies include Java, Spring Boot, Kubernetes, and cloud platforms, with Kafka, Cassandra, Spark, Scala, and HDFS preferred.

Develops secure, scalable full-stack software solutions within an agile team. Responsibilities include designing applications, writing and troubleshooting production code, creating architecture artifacts, analyzing data for system improvements, and maintaining operational resiliency. The role requires Java, React, and Spring experience, software development lifecycle knowledge, testing, application security, CI/CD, and responsible use of AI-assisted development tools.

Designs, develops, tests, troubleshoots, and maintains secure, scalable cloud-native software solutions. Creates architecture and design artifacts, develops Python and data-intensive applications on AWS and Databricks, builds AWS Glue jobs, and improves system reliability through data analysis, automation, and responsible AI-assisted development. Collaborates within an agile environment while supporting software delivery, security, resiliency, and operational stability.

Develops and maintains secure, scalable Python and AWS applications within an Applied AI/ML engineering team. Responsibilities include system design, architecture, testing, troubleshooting, code reviews, agile planning, MLOps integration, reliability collaboration with SRE teams, and analyzing data to improve application quality and system architecture. The role also requires responsible use of AI-assisted development tools and collaboration with data scientists.

Build, operate, and scale AWS production environments using EKS, ECS, and Terraform. Maintain CI/CD pipelines, Akamai CDN and security configurations, certificates, monitoring dashboards, alerts, and incident-response processes. Improve reliability, observability, automation, resiliency, and secure operations for application and AI-enabled services. Support change management, troubleshooting, documentation, root-cause analysis, and responsible use of AI-assisted development tools.

Develop and maintain scalable AEM as a Cloud Service applications for client-facing digital experiences. Responsibilities include software design, development, testing, troubleshooting, performance optimization, secure coding, AI-assisted development, and collaboration with agile engineering and product teams. The role requires expertise in AEM templates, components, client libraries, widgets, deployment processes, and headless capabilities, while supporting application resiliency and continuous delivery.

Develops secure, scalable full-stack software for payments technology using Python and React. Designs application architecture, writes and troubleshoots production code, builds automated tests with Playwright and Pytest, and supports operational stability. Uses AI-assisted development tools responsibly to improve coding, testing, and documentation while validating outputs for security and correctness. Analyzes data, creates visualizations, and identifies patterns that improve software quality and system architecture within an agile SDLC environment.

Designs, develops, tests, troubleshoots, and operates secure, scalable software across firmwide platforms. Builds backend services, GraphQL and REST APIs, React interfaces, micro-frontends, static content pipelines, integrations, search and discovery features, and notification workflows. Contributes across the full SDLC in an agile environment, analyzes data to improve systems and coding practices, creates architecture artifacts, and uses authorized AI-assisted development tools responsibly.

Lead software engineering efforts within JPMorganChase’s Commercial and Investment Bank Technology team. Responsibilities include designing, developing, testing, securing, debugging, and operating production software; improving automation and resiliency; adopting responsible AI-assisted development practices; coaching engineers; and evaluating vendor and architectural solutions. The role requires advanced programming, cloud-native development, SDLC expertise, agile practices, and financial services technology knowledge.

Design and develop secure, scalable software using Java, microservices, messaging, cloud services, business rule engines, and responsive web technologies. Build distributed systems, automate infrastructure and deployments, modernize legacy applications, optimize databases and models, and maintain CI/CD pipelines. Document architecture, conduct risk analyses, analyze data, refactor code, validate requirements, support production deployments, and resolve integration issues across business and technology teams.

Design, build and enhance large-scale marketing and events data platforms. Ingest, transform and validate data on AWS/Databricks, implement/optimize ETL, enforce data quality, write services and automation, and collaborate in Agile teams to deliver production solutions.

Designs, develops, tests, and maintains scalable, secure systems using Java or Python; applies enterprise AI-assisted coding tools; contributes to architecture, data-driven improvements, CI/CD, and resilient production delivery within agile teams.

Build and operate scalable machine learning training platforms and pipelines across AWS and other cloud environments. Optimize GPU-based single-node and distributed training for performance, cost, stability, and reproducibility. Develop Kubernetes infrastructure, GenAI and LLM fine-tuning workflows, observability, CI/CD automation, governance controls, and developer self-service tools. Partner with data engineering and platform teams while applying secure, responsible AI-assisted development practices.

Build and maintain Java and Kotlin JVM microservices for fixed-income portfolio management, analytics, reporting, trade sizing, exposure monitoring, order management, scenario analysis, compliance checks, and order submission. Design resilient REST APIs, relational database schemas, SQL queries, and migrations. Contribute to architecture, testing, operational stability, data analysis, secure AI-assisted development, CI/CD, and agile engineering practices.

Designs, develops, tests, troubleshoots, and maintains secure, scalable software solutions within an agile DevOps team. Builds production code, creates architecture and design artifacts, supports operational stability, analyzes data for system improvements, and contributes to engineering communities. Requires AWS and Terraform experience, programming proficiency, software development lifecycle knowledge, and familiarity with CI/CD, application resiliency, and security.

Design and implement scalable, fault-tolerant Kubernetes control-plane components. Develop Helm charts, custom controllers and CRDs, build deployment automation, monitoring, dashboards, and participate in on-call operations to ensure platform reliability and operability.

Design, build, and deliver production AI/ML solutions using agile practices. Translate business requirements into ML specifications, produce secure high-quality code, create architecture artifacts, analyze large datasets, troubleshoot complex issues, and contribute to engineering communities and continuous improvement.

Design, build, and maintain reliable, secure, and scalable platform software within an SRE/DevOps environment. Implement observability, CI/CD, container orchestration, cloud services, and AI-assisted development practices while mentoring engineers and improving system resilience and automation.

Build, design, and maintain a managed AWS Databricks data platform. Provide platform administration, workspace configuration, resource monitoring, and engineering support to SRE, data engineering, and ML teams. Develop and troubleshoot Python/Java applications, use CI/CD and artifact integrations, leverage Spark and Terraform, and apply enterprise AI-assisted development tools while ensuring secure, resilient, and compliant engineering practices.

Lead contributor designing, building, and operating low-latency trading compute infrastructure. Responsibilities include server hardware strategy, OS tuning, automation, build/configuration management, log/metric aggregation, vendor evaluation, developing secure production code, troubleshooting, and driving engineering best practices across teams.

Leads end-to-end architecture and development of secure, scalable enterprise software using Java, Spring Boot, and Python. Defines APIs, integrations, distributed systems, data patterns, and operational requirements. Provides hands-on technical leadership, resolves production issues, establishes engineering standards, and productionizes AI/ML capabilities with responsible AI controls. Partners with data science teams on model deployment, monitoring, and lifecycle management while driving modernization, DevOps, resiliency, and observability practices.

Leads engineering for a regulatory and financial reporting platform. Designs scalable architecture and infrastructure, develops secure Python or Java applications, applies AI-assisted development and agent workflows, and supports deployment, monitoring, reliability, and operational stability. Partners with technology, product, and reporting stakeholders on data flows, controls, integrations, and reporting solutions. Requires strong cloud, DevOps, SQL, data modeling, and regulatory reporting expertise.