Artificial Intelligence Jobs in Jersey City, NJ

The AI Product Owner leads AI-driven initiatives in Underwriting and Claims, collaborating with stakeholders to define product requirements, prioritize AI opportunities, and ensure successful implementation and adoption of AI solutions.

The AI Product Owner will lead the lifecycle of AI products, partnering with business stakeholders, translating needs into requirements, and ensuring successful implementation and adoption of AI solutions.

Lead customer-facing, consultative upsell efforts for AI legal solutions at law firms: drive discovery, map workflows, design demos and POCs, influence stakeholders, and partner with sales/product to close and ensure adoption.

As a Junior AI Data Engineer, you will participate in the implementation of AI applications, focusing on data quality auditing, model evaluation, and performance testing.

Lead research, design, and deliver Pearson's scalable learner model and AI-driven features. Partner with product, engineering, and design to define data requirements, build prototypes, maintain data pipelines, ensure data quality, and translate research into production ML capabilities and business growth.

Lead and support IT and AI sourcing from intake through contract execution: develop sourcing strategies, run RFx events, perform spend and market analysis, negotiate vendor and software agreements, manage vendors, collaborate with Legal/Finance/Technology, drive cost savings and process efficiencies, and present recommendations to stakeholders and leadership.

Lead strategy and delivery for an AI-powered claims decision-support and auto-adjudication platform. Define vision and roadmap, manage a team of product managers, partner with business, engineering, and data science, and drive adoption, impact measurement, and executive-level communication across a complex, matrixed enterprise.

Design and build AI-powered tools to accelerate incident detection, triage, root-cause analysis, and automation for Credit trading production. Partner with support, development, and AI teams to embed AI into workflows, maintain high availability, analyze logs/metrics, and measure reductions in MTTR and operational toil.

Principal AI Forward-Deployed Engineer designs and builds production-grade AI and agentic systems, leads forward-deployed projects with business stakeholders, authors scalable cloud architectures (AWS), implements MLOps/DevOps best practices, and ensures operational excellence, security, and measurable business outcomes.

The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.

Lead architecture and implementation of cloud-native, AI-powered web applications. Integrate LLMs, vector search, RAG pipelines, model serving and real-time data. Design end-to-end frontends and backends, build Python backend services integrated with React/Angular, ensure CI/CD and testing, and lead cross-functional teams to deliver scalable production solutions.

As an AI Engineer Intern, you'll assist with building AI solutions, testing ML techniques, managing datasets, and contributing to production AI systems while gaining hands-on experience in a collaborative environment.

The AI Engineer Intern will assist in building and testing AI/ML solutions, contribute to production AI systems, and explore agentic AI frameworks, gaining hands-on experience in a dynamic environment.

The AI Solutions Director manages AI POD teams, leading complex customer pursuits, ensuring pipeline growth, revenue attainment, and mentoring team members in consultative selling.

The AI Solutions Architect specializes in pre-sales technical solutions for AI platforms, collaborating on architectural designs, conducting customer engagements, and ensuring seamless transitions to delivery teams.

The AI Services Consultant develops and positions AI consulting services, collaborates across teams, and manages client engagements to unlock AI potential and drive value through structured proposals and delivery.

The AI Solutions Architect engages in technical pre-sales, designing AI architectures, conducting technical discovery sessions, and collaborating on proof-of-concept projects while ensuring smooth transitions to delivery teams.

The AI Services Consultant scopes and positions AI consulting engagements, collaborates with sales and delivery teams, and develops service proposals to drive AI initiatives and infrastructure investments.

The AI Solutions Executive drives AI sales by generating opportunity pipelines, implementing effective sales strategies, and collaborating with field teams to close various AI solutions.

The AI Development Specialist enables enterprise development teams by selling coding assistant and AI-native engineering solutions while collaborating with NVIDIA teams to enhance application performance.

The AI Solutions Executive generates and closes AI pipeline, collaborates with field sales, builds customer relationships, and delivers tailored presentations and proposals.

Lead the design and optimization of batch and streaming data pipelines, ensuring high-quality data delivery for AI and analytics, while mentoring and promoting engineering best practices.

Lead a ~70-person engineering organization to transform Master and Reference Data development into an AI-first operation. Set multi-year AI roadmap, embed generative and agentic AI across the SDLC, modernize Scala-based data platforms (Scala, Akka, Spark), ensure delivery excellence (CI/CD, test automation), apply LLMs for entity resolution and data quality, partner with governance and product teams, and drive talent, metrics, and risk/compliance management.

Design and implement full-stack applications for GenAI, build developer tooling, collaborate with product teams, and enhance AI agent delivery.

As a Principal Solution Architect, you will help teams design and implement scalable AI solutions, mentor engineers, and drive platform evolution in healthcare, legal, and compliance. Collaboration with product teams is key for designing secure, reliable architectures and demonstrating platform capabilities through prototypes.