Software Engineer Jobs in Jersey City, NJ

Lead development and delivery of secure, production-grade AI-enabled applications. Design, code, test, and operate AI features; drive adoption of AI-assisted engineering practices; evaluate model safety and integrations; automate remediation and reliability; coach teams on responsible AI, secure coding, and CI/CD for cloud-native environments.

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 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 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 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 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).

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.

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, 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, 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 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 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.

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 and mentor a software engineering team to design, build, and operate secure, scalable cloud-native applications using Java and Python. Drive architecture reviews, CI/CD automation, observability, AI-assisted engineering practices, and data governance while ensuring operational stability and compliance.

Lead a UI team to design, prototype, and deliver scalable, reusable React/TypeScript user interfaces and micro-frontend solutions. Build component libraries, ensure accessibility and performance, collaborate with UX, backend, and DevOps, and mentor junior developers.

Lead software engineer responsible for designing, developing, and delivering secure, scalable Java/Spring Boot/React applications. Drives CI/CD, automation, operational stability, vendor evaluations, and engineering communities of practice.

Lead and mentor engineers to design, build, and optimize Databricks/Spark ETL pipelines and AWS-based data lake/warehouse solutions. Drive observability, automation, resiliency, performance tuning, and reusable data engineering patterns across teams.

Lead development of AI‑first analytics and data products, modernize the data mesh, build autonomous human‑in‑the‑loop agents for schema drift and governance, design scalable batch and real‑time pipelines, enforce lineage/DQ/governance, and provide technical leadership across analytics, platform, risk, and domain teams.

Lead an agile engineering team to design, build, and maintain secure, scalable Java Spring Boot microservices. Deliver production-quality code, drive architecture and vendor evaluations, mentor developers, improve operational stability, and promote best practices for testing, CI/CD, security, and cloud-native deployments in the financial services domain.

Lead technical delivery for analytics-focused software: design, develop, test, and operate secure, high-quality production code. Drive automation and CI/CD, evaluate vendor/architecture choices, mentor junior engineers, and promote resilient cloud-native solutions within financial services technology teams.

Lead design, development, and operation of large-scale Spark-based data pipelines and lakehouse solutions. Write and review Python/PySpark and Spark SQL production code, optimize Spark workloads on EMR/Databricks, manage Apache Iceberg table operations, drive AI-assisted engineering adoption, automate reliability and CI/CD practices, and lead technical evaluations and communities of practice.

Lead design and implement scalable, secure ML and LLM-powered solutions on cloud. Produce production-quality Python code, build data pipelines and model inference services, drive AI governance and SDLC best practices, mentor teams, and collaborate cross-functionally to operationalize GenAI capabilities.

Lead an agile payments engineering team building secure, scalable Java/Spring microservices. Be hands-on (50% coding), perform design, code reviews, and debug. Drive adoption of enterprise AI-assisted development practices, ensure CI/CD, resiliency, operational stability, mentor engineers, evaluate vendors, and manage stakeholders to meet compliance and business SLAs.

Lead development of secure, high-quality production software for analytics and credit risk; design, code (Python/Java), review, troubleshoot, automate remediation, drive CI/CD and cloud-native solutions, mentor junior engineers, evaluate vendors, and promote new technologies.