Software Engineer Jobs in Jersey City, NJ

Lead software engineer responsible for designing, developing, and troubleshooting end-to-end solutions across z/OS mainframe and Java platforms. Drive automation, CI/CD, observability, and secure engineering practices. Lead adoption of enterprise-authorized AI-assisted engineering tools, evaluate vendor solutions, mentor teams, and promote engineering excellence within agile delivery.

Lead technical delivery of secure, scalable software and automation across the SDLC. Design, develop, review, and debug production code; drive automation to remediate recurring issues; lead vendor evaluations and engineering communities; govern AI-assisted engineering practices and cloud-native solutions to improve resiliency, security, and delivery outcomes.

Lead development and delivery of KDB-based real-time processing systems. Provide technical direction, write and review production code, optimize large-dataset query performance, ensure scalability, resiliency, and CI/CD, mentor team members, manage delivery planning and testing, and advocate firmwide engineering practices.

Lead technical contributor driving design, development, and operational stability of production software. Builds secure, high-quality code, automates remediation, champions AI-assisted engineering practices, evaluates vendor architectures, and leads engineering communities to adopt resilient, secure CI/CD and cloud-native solutions in a financial-services environment.

Lead firm-wide adoption and operationalization of AI/LLM-enabled software engineering across the SDLC/PDLC. Design and scale agentic systems, orchestration, guardrails, monitoring, and secure integrations. Partner with platform and App Dev leaders to deliver production-grade, auditable AI workflows that reduce developer toil, improve reliability, and meet governance, security, and observability standards.

Lead technical design and delivery of secure, scalable microservices and web applications. Develop, review, and troubleshoot production code; drive architectural evaluations, automation, operational stability, and responsible AI-assisted engineering practices.

Design and deliver a composable per-PR virtual environment platform: architect traffic isolation, dependency-graph intelligence, data and lifecycle management, CI/CD integration, hybrid provisioning (Kubernetes, VMs, cloud/on-prem), observability/SLOs, and drive adoption at scale while governing AI-enabled engineering workflows and responsible AI controls.

Design, build, and optimize low-latency, high-throughput Spring Boot distributed services and cloud-native AWS architectures. Implement IaC (Terraform/CloudFormation), observability (Datadog/Dynatrace/Splunk), and containerized deployments. Own production reliability, mentor engineers, lead standards, and drive adoption of AI-assisted engineering practices and secure, scalable ML platform solutions.

Lead design, development, deployment, and operation of security monitoring controls and tooling (API-first, microservices) with focus on blockchain security. Build CI/CD pipelines with automated testing and security guardrails, implement secure SDLC practices, integrate blockchain security telemetry, automate remediation, and provide SME input during vendor evaluations and proofs-of-concept.

Lead design, build, and operate Databricks Lakehouse data platforms on AWS. Maintain high-scale batch and streaming pipelines, enforce governance/security, optimize Spark/Delta performance, ensure reliability, and mentor engineering teams.

Lead an agile engineering team to architect, develop, and productionize secure, scalable software that integrates LLMs and generative AI. Drive AI-assisted engineering practices, mentor engineers, translate business requirements into technical roadmaps, automate reliability, and ensure compliant, high-quality delivery.

Lead engineer responsible for deploying and serving end-to-end ML models and cloud-native services, driving AI-assisted engineering practices, producing secure, high-quality production code, influencing product design and operations, and mentoring technical teams.

Lead design, build and operate scalable AI/ML data platform solutions; run production incident management; implement SRE practices, observability and resiliency; drive adoption and governance of enterprise AI-assisted development tools; mentor engineers and reduce operational toil via automation.

Lead design, implementation, and management of large-scale mainframe systems; ensure performance, reliability, security, and data integrity. Mentor global teams, integrate AI-assisted tools and distributed technologies, drive SDLC automation and validation, troubleshoot production issues, and communicate progress to stakeholders.

Design, build, and operate AI-enabled applications and ML/LLM platforms. Deliver production-quality code, SDK/REST integrations, MLOps pipelines, model/versioning and CI/CD, distributed fine-tuning and evaluation, and reusable platform components. Drive adoption of agentic AI workflows, enforce responsible AI and security controls, automate reliability, and influence senior stakeholders to align platform roadmaps with business outcomes.

Lead architecture and implementation of scalable, secure engineering frameworks and production code for data-intensive and LLM-based systems. Design and govern agentic AI, RAG/embedding pipelines, model serving, observability, and cloud-native platforms. Mentor engineers, set engineering standards, advise stakeholders, and drive adoption of AI-enabled development practices and responsible AI controls in regulated financial environments.

Lead design, build, and operate scalable, resilient cloud-native Java microservices. Produce high-quality secure code, drive CI/CD and automation, manage Kubernetes deployments on AWS, champion AI-assisted engineering practices, evaluate vendors, and improve operational stability and team standards.

Lead design, development, and support of a cloud-native Trade Execution Platform. Deliver secure, resilient production code, drive CI/CD and resiliency practices, champion enterprise-authorized AI-assisted engineering, automate remediation, and partner with stakeholders to improve stability and delivery.

Lead and contribute to design, architecture, and delivery of loan management platforms. Drive a greenfield initiative to transform legal-document storage using AI. Provide technical guidance, re-architect systems for scalability and stability, collaborate with global stakeholders, mentor teams, and champion SDLC best practices.

Lead backend engineer responsible for designing, developing, and delivering secure, scalable Java/Spring Boot services on cloud infrastructure. Drive event-driven, multi-region architectures, operational stability and automation, lead architectural evaluations, mentor engineering communities, and incorporate AI/LLM tools.

Lead development of fraud protection microservices: design, implement, benchmark, and optimize scalable secure systems on AWS. Drive performance best practices, adopt enterprise AI-assisted engineering, mentor teams, and collaborate with stakeholders to ensure application resiliency and operational stability.

Lead design and delivery of agentic LLM systems to translate mainframe logic into verified modern services. Build ingestion, RAG pipelines, multi-agent orchestration, evaluation/verification harnesses, runtime platforms, ETL/CDC integrations, and operate LLMOps for production reliability while partnering with domain SMEs and driving AI-assisted engineering governance.

Lead technical design and deliver secure, scalable production software. Develop, review, and debug code; improve operational stability via automation; evaluate vendor architectures; promote AI-assisted engineering practices and responsible AI usage; lead engineering communities of practice and apply cloud-native and infrastructure expertise (Hyper-V, OpenShift).

Lead design, develop, and troubleshoot secure, high-quality Java/Python applications and microservices on AWS. Drive adoption of enterprise AI-assisted engineering practices, automate recurring fixes, improve operational stability, evaluate vendor/architecture fit, and lead cross-team communities of practice while promoting inclusive team culture.

Lead design and delivery of secure, scalable data-intensive and LLM-based production systems. Build agentic AI, RAG/embedding pipelines, model serving, observability, and automation; mentor engineers; drive AI-assisted development governance and SDLC best practices.