Software Engineer Jobs in Jersey City, NJ

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 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 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 engineering role building and evolving the Sigma data-visualization platform: develop C++/Rust->WASM engine, integrate Apache Arrow, build TypeScript/React (Next.js) front-end, extend data adapters, tune WASM performance, ensure secure high-quality production code, drive architecture decisions, evaluate vendors, and lead engineering communities to improve operational stability.

Lead and mentor a team to design, build, and operate agentic LLM systems and production LLM-backed APIs. Own end-to-end ML lifecycle, MLOps, inference optimization, vector memory, safety/guardrails, and cross-functional governance for scalable, secure AI deployments.

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 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.

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 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.

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 and contribute to an agile engineering team building scalable, secure big-data applications. Provide technical guidance, design and produce production-quality code, drive architecture and tooling decisions, champion AI-assisted engineering practices, and collaborate across global teams to ensure operational stability and delivery.

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 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 design and implementation of scalable, cloud-native systems using Go and IaC. Provide technical direction, produce secure production code, promote AI-assisted engineering practices, drive cloud migrations, and act as a subject-matter expert across the SDLC.

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 an agile team to design, develop, and maintain low-latency front-office systems for loan trading, risk and P&L. Produce secure, high-quality production code, troubleshoot end-to-end dependencies, automate remedial work, evaluate vendor architectures, and translate business needs into technical solutions.

Lead backend engineering efforts on an agile team: design, develop, test, and operate secure, resilient Java-based systems. Provide technical guidance, promote enterprise SDLC and AI-assisted development practices, drive automation/CI-CD, manage containerized deployments with Kubernetes, and influence engineering decisions across teams.

Lead design and implement scalable hybrid cloud solutions for transactional, analytics, and RAD workloads. Write and review code, drive AI-assisted engineering adoption, apply SDLC tools, collaborate with leads and stakeholders, conduct code reviews, present technical updates, prioritize work, and mentor team members.

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 team to design, build, optimize, and operate scalable back-end and web UI systems using Java/Spring and React. Drive adoption of AI-assisted engineering practices, ensure secure and resilient solutions, collaborate with architects, product specialists, and global teams, and present demos to stakeholders.

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.

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 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.