Software Engineer Jobs in Jersey City, NJ

Lead architecture, design, and development of Java/Spring back-end services and shared frameworks. Mentor agile teams, produce secure high-quality code, optimize performance, implement observability, and drive adoption and governance of AI-assisted engineering practices and SDLC automation.

Lead backend engineer responsible for designing, developing, and operating secure, scalable Java/Spring Boot services using Kafka and NoSQL stores; drive architecture reviews, operational stability, AI-assisted engineering adoption, and cross-team technical leadership.

Lead development of secure, production-grade storage/platform software. Design and deliver distributed systems using Python and modern cloud-native practices, drive automation and AI-assisted engineering adoption, troubleshoot complex incidents, mentor engineers, and partner across product, operations, and security to improve reliability and delivery.

Lead design and deliver secure, scalable production systems for banking data technology. Provide technical guidance, write and review high-quality code, drive product and architecture decisions, champion firmwide engineering practices (CI/CD, resiliency, security), and contribute as a subject-matter expert across streaming, cloud-native, and low-latency data platforms.

Lead development of high-performance, scalable software frameworks that optimize ML training and inference on accelerator-based architectures. Mentor engineers, advise cross-functional teams, apply HPC and telemetry-driven decisions, and publish reusable performance patterns for low-latency, throughput, and power-efficient solutions.

Lead architecture, design, and delivery of scalable Markets Data Lake and data/AI platform components. Build Python-based microservices and real-time Kafka services, integrate with JPMC Athena and data platforms, mentor teams, set engineering standards, and drive cloud big-data solutions on AWS.

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 cloud infrastructure and developer experience tooling. Drive CI/CD, DevSecOps, observability, AI-assisted coding workflows, and integrations for AI agents and MCP to accelerate platform automation and developer productivity.

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 architecture and hands-on delivery of production-grade LLM and agentic AI platforms: design cloud-native AWS services, retrieval and RAG, observability, evaluation frameworks, secure APIs, performance/cost optimization, and mentor senior engineers while defining engineering standards for reliable, safe AI operations.

Build and operate secure, resilient AWS cloud foundation services using Java/Go. Design, develop, test, and automate production code, reduce operational burden, lead architecture/vendor evaluations, promote AI-assisted engineering practices, and drive reuse and validation standards across teams.

Lead design and build of a production multi-agent AI platform: own architecture and strategy, write Python production code, define agent toolchains, RAG pipelines, state management, distributed ingestion, evaluation and feedback loops, and partner on MLOps and deployment while mentoring engineers and ensuring production reliability and security.

Lead engineering efforts to design, build, and maintain AEM-based web applications; deliver secure, high-quality code; drive AI-assisted development adoption; integrate Adobe marketing tools; ensure resiliency, accessibility, SEO, and performance; automate recurring remediation; evaluate vendors and coach teams on responsible AI and security within financial services.

Lead an agile engineering team to design, build, test, and operate secure, scalable Java-based systems. Provide technical guidance, drive architecture and tooling decisions, adopt AI-assisted development practices, ensure CI/CD and resiliency, and manage containerized deployments (Kubernetes). Advocate firmwide SDLC standards and mentor engineers.

Lead design, build, and operate scalable data platform components and pipelines (batch and real-time) using Spark, Flink, Kafka, Airflow and Databricks. Implement data modeling, governance, cataloging, observability, and production-grade code; partner with stakeholders and lead technical evaluations and communities of practice.

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 backend engineer responsible for designing, building, and operating scalable, secure microservices for equities broker-dealer and prime finance platforms. Integrate AI/ML and GenAI (LLMs, RAG, embeddings, vector DBs) into production, drive architecture decisions, ensure SDLC and operational stability, mentor teams on responsible AI use, and collaborate with product and operations to deliver high-volume, low-latency financial systems.

Lead architecture and delivery of production-grade agentic AI and NLP solutions for client onboarding. Design reusable frameworks (RAG, multi-agent orchestration, LLMs), integrate agents into enterprise systems, define safety/guardrails, advise stakeholders, and champion AI-assisted SDLC improvements to improve delivery, quality, and operational outcomes.

Lead design, develop, test, and operate ultra-low-latency C++ trading connectivity and risk modules on Unix/Linux. Integrate FPGA pipelines with C++ for deterministic performance, automate remediation, establish latency/throughput/resiliency tests, and drive AI-assisted engineering adoption across the team.

Lead technical design, development, and operational stability of asset and wealth management systems. Drive adoption and validation standards for enterprise-authorized AI-assisted engineering, set reference architectures across Java, React, Kafka, Oracle/Aurora, Airflow, and Spark, guide cloud deployments, automate remediation, and evaluate vendors and integration approaches.

Lead software engineer responsible for designing, implementing, and operating a managed Spark/Databricks on Kubernetes data platform in AWS. Build production-grade cloud solutions, automate operational stability, support data engineering and ML teams, drive vendor evaluations, and promote enterprise AI-assisted engineering practices.

Lead design and implementation of a large-scale Marketing and Events data platform. Build and transform ETL on cloud/Databricks, ensure data quality, automate pipelines, enforce data standards, and deliver solutions using agile practices while mentoring and hiring team members and partnering with stakeholders.

Lead design, development, and production support of secure, cloud-native data and analytics systems. Drive adoption of AI-assisted engineering practices, improve automation and resiliency, evaluate vendor solutions, and mentor teams on secure, scalable software delivery.

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.