Software Engineer Jobs in Jersey City, NJ

Leads software engineering strategy and delivery for post-trade technology, including system design, application development, testing, operational stability, and cross-functional leadership. Establishes governance for agentic AI-enabled engineering and SDLC automation, emphasizing secure validation, resiliency, traceability, and measurable outcomes. Delivers scalable solutions across business domains while influencing senior stakeholders. Preferred expertise includes Core Java, C/C++/C#, Kafka, MQ, FIX, MongoDB, Cassandra, Sybase modernization, performance tuning, concurrency, and resilient system design.

Lead the design, development, and operation of secure, scalable AI/ML cloud platforms. Build infrastructure, automation, APIs, deployment workflows, and GPU-enabled environments for model training and inference. Drive reliability, observability, cost optimization, incident response, and enterprise LLM operationalization. Partner with data science and engineering teams while promoting responsible AI-assisted development, secure coding, automated testing, and production-quality delivery.

Leads design and development of real-time, mission-critical software using Java and Kafka. Provides technical leadership across system design, application development, testing, cloud-native delivery, resiliency, security, and performance optimization. Promotes AI-assisted engineering practices, validates AI outputs, evaluates architecture and vendors, and mentors teams through communities of practice. The role operates within an agile financial services technology environment.

Designs, develops, reviews, and maintains scalable, highly available software applications across digital channels. Responsibilities include creating technical specifications, writing maintainable code, evaluating architectural solutions, participating in Scrum ceremonies, managing user stories and tasks, monitoring development progress, and mentoring junior engineers. The role requires experience with Claude Code or Google Gemini, modern programming languages, web services, cloud platforms, and software architecture.

Design and build secure, scalable enterprise clinical workflow systems for Butterfly Cloud. Solve distributed-systems challenges involving elasticity, reliability, performance, and automated validation. Lead system design, own business problems, guide developers through execution, and mentor engineers. The role may span frontend and backend layers and involve cloud architecture, observability, search, real-time applications, GraphQL, containerization, and healthcare data compliance.

Participate in a two-day social-impact hackathon building tech solutions for nonprofits. Develop, test, and troubleshoot software; write secure code; collaborate with engineers and stakeholders; use automation and approved AI development tools responsibly; attend training and mentorship; and potentially be considered for a 2027 Software Engineer Program Summer Internship.

Develops and maintains software solutions across full-stack applications and infrastructure. Responsibilities include hands-on Java and Python coding, Kafka and API development, database work, CI/CD pipeline maintenance, testing, troubleshooting, system design, and translating business requirements into technical solutions. Works in Agile teams, follows security and development standards, supports production systems, estimates project work, and mentors junior associates.

Lead software engineering for JPMorganChase’s Corporate Data and Analytics Services team. Design, develop, test, troubleshoot, secure, and maintain scalable production systems using Java, Python, AWS, and agile SDLC practices. Review code, improve resiliency and automation, remediate recurring issues, and promote responsible AI-assisted engineering practices. Lead architectural evaluation sessions with vendors and internal teams while coaching engineers on secure, compliant AI tool adoption.

Leads architecture, development, deployment, and optimization of enterprise LLM and GNN serving platforms across AWS, cloud, and on-premises environments. Establishes MLOps and LLMOps strategies, agentic AI engineering standards, automation, governance, observability, and operational practices. Optimizes inference for throughput and latency using Triton and vLLM, partners with data science and SRE teams, and influences senior stakeholders on secure, responsible AI adoption.

Hands-on technical lead designing, building, and optimizing high-performance Linux compute platforms for low-latency electronic trading. Responsibilities include kernel- and hardware-level performance tuning, containerization, IaC and CI/CD design, automation and tooling development, vendor interfacing, AI-assisted engineering governance, and mentoring cross-functional engineering teams to deliver reliable, low-latency infrastructure.

Lead technical design, develop and deliver resilient backend services and automation pipelines. Write, review, and debug production-quality Java Spring Boot code, improve operational stability through automation, and drive architecture and delivery decisions within an agile team in a regulated enterprise environment.

Lead technical direction and deliver secure, scalable cloud platform capabilities for AWS networking, EC2, and storage. Own Terraform strategy and enterprise IaC, build automation and services in Python, enforce secure-by-default designs, drive reliability and standardization, mentor engineers, and partner with architecture and security teams.

Lead design and delivery of developer platform capabilities for AWS networking, compute, and storage. Build and maintain Terraform IaC, develop automation and services in Python, implement secure-by-default patterns, improve reliability, review code, and mentor engineers while partnering with architecture, security, and application teams.

Designs, develops, debugs, and delivers secure, production-grade full‑stack Java/Spring Boot and React applications. Leads technical evaluations, drives automation and CI/CD, improves application resiliency and operational stability, and promotes best practices across engineering teams.

Lead full-stack engineer responsible for designing, developing, testing, and operating secure, scalable applications. Drive adoption of AI-assisted engineering practices, improve operational stability through automation, lead vendor and architecture evaluations, and coach teams on secure, compliant AI use. Contribute high-quality production code, code reviews, and technical troubleshooting across the SDLC within financial services contexts.

Lead design and delivery of secure, scalable full-stack solutions. Develop, review, and troubleshoot production code; drive automation and CI/CD; champion AI-assisted engineering practices; evaluate vendor and architectural options; mentor teams and promote resilient, reusable design patterns across the organization.

Lead full-stack software engineering initiatives using Java, Spring Boot, React, and AWS. Design and deliver secure, scalable services and web applications, create architecture artifacts, troubleshoot production issues, improve automation and observability, and lead technical design decisions. Mentor team members, guide responsible use of AI-assisted development tools, analyze application data, and improve operational stability, resiliency, and coding practices within an agile financial-services environment.

Lead development of secure, scalable full-stack applications for JPMorgan Chase’s Asset and Wealth Management client services platform. Responsibilities include Java, Spring, React, cloud architecture on AWS, SQL and Snowflake data solutions, testing, deployment, operational stability, and system modernization. The role leads AI-assisted engineering practices, collaborates with product owners and global stakeholders, supports agile delivery, and serves as a primary technical and product contact.

Lead design, development, testing, and production support of enterprise Java web applications. Collaborate with stakeholders on requirements and architecture, write code and tests, perform code reviews, support integration/UAT/performance testing, and drive adoption of enterprise AI-assisted engineering practices and SDLC automation.

Lead design, implement, and operate Hyper-V cluster lifecycle automation: provisioning, configuration, patching, compliance, decommissioning, and orchestration. Drive AI-assisted engineering practices, production deployments, troubleshooting, and data-center-scale automation while ensuring security, scalability, and cross-team collaboration.

Lead software engineers and applied AI/ML practitioners while developing secure, scalable production systems in Java or Python. Integrate LLMs, generative AI, NLP, RAG, and coding assistants into software engineering workflows. Establish responsible AI governance, validation standards, testing, security, and operational practices. Guide system architecture, experiments, algorithm implementation, productionization, code quality, automation adoption, and technical decision-making across global teams.

Lead design, development, troubleshooting, and deployment of automation for virtualized clusters and Kubernetes or OpenShift lifecycle operations. Build scalable server-side services, automate provisioning and compliance workflows, improve operational stability, and manage distributed systems using workflow orchestration. Promote responsible AI-assisted engineering practices, establish validation standards, document technical decisions, and mentor engineers through design and code reviews.

Leads the design and development of secure, scalable software frameworks and production systems. Builds reusable engineering platforms, reviews code, improves SDLC automation, and governs agentic AI-enabled development workflows with responsible AI, security, resiliency, auditability, and human-in-the-loop controls. Advises cross-functional teams, solves complex technical problems, promotes cloud-native practices, and influences senior technology and business leaders.

Lead design, build, and operate AI-driven automation and infrastructure tooling. Develop secure production code, deploy on Kubernetes, define observability/SLOs, drive AI-assisted engineering adoption, and lead cross-team technical decisions.

Leads design, development, deployment, and support of Privileged Access Management solutions. Provides technical leadership across security architecture, integrations, testing, automation, cloud platforms, and operational stability. Partners with stakeholders and vendors, performs proofs of concept, documents implementations, and provides Level 3 support. Drives secure, responsible adoption of AI-assisted engineering practices, validates AI outputs, and coaches teams on compliant usage.