Artificial Intelligence Jobs in Jersey City, NJ

Lead design, build, and operation of scalable, secure AI-enabled platforms; mentor engineers; ensure reliability, security, and delivery of conversational AI and cloud-native solutions; collaborate cross-functionally to translate use cases into platform capabilities.

Serve as a Microsoft Dynamics 365 functional lead delivering CRM/ERP assessments, design, configuration, fit-gap analysis, data migration, testing, training, and client-facing implementation support. Lead project tasks, create functional requirements and process flows, support proposals and business development, and coach junior staff to deliver solutions leveraging Microsoft platforms.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead finance-focused consulting engagements to analyze financial data, design performance management frameworks, and drive budgeting, forecasting, and financial planning. Manage teams, mentor junior staff, build client relationships, deploy data visualization solutions, and identify cost-reduction and process optimization opportunities to improve enterprise financial performance.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Build and manage InvestCloud’s commercial transfer agent network for the Altic private markets platform. Responsibilities include identifying and prioritizing transfer agent partners, structuring and negotiating pricing and contracts, coordinating with Legal, managing long-term relationships, overseeing renewals and escalations, and coordinating handoffs to Product and Engineering for integration. The role requires US asset management and transfer agency expertise, commercial partnership experience, and use of AI-enabled research tools.

Lead supply chain analytics consulting engagements, offshore teams, and client discussions. Translate supply chain business challenges into scalable data and analytics solutions using Python, SQL, machine learning, AI, optimization, and operations research. Provide domain expertise across demand and supply planning, shipping, and inventory management; mentor analysts and data professionals; architect analytics frameworks; and communicate actionable insights to business stakeholders.

Summer Analyst in Data & AI will design and build end-to-end data, analytics, and ML/AI solutions using cloud and modern tooling. Responsibilities include developing models and pipelines, running experiments tied to business KPIs, supporting data governance and compliance, creating dashboards, and collaborating in agile teams while receiving mentorship and training.

Leads and builds the pharmaceutical Business Intelligence and Analytics function, partnering with commercial leadership and cross-functional teams. Owns data strategy, integration, reporting, dashboards, forecasting models, market research, patient-finding analytics, omnichannel measurement, field-force reporting, and business development assessments. Uses SQL Server, Excel, Tableau or Power BI, advanced analytics, AI, and machine learning to generate actionable insights, improve patient access, and support commercial decisions.

Participate in an 18-month rotational early-career program supporting asset servicing, custody, clearance, and settlement operations. Analyze processes, operational risks, controls, and data to identify improvements using automation and AI. Support daily operations, continuous improvement initiatives, cross-functional collaboration, and stakeholder communications while developing knowledge of financial markets, regulation, and business workflows.

Leads enterprise architecture strategy, standards, governance, target-state designs, and modernization roadmaps across applications, data, AI, cloud, security, platforms, and integration. Advises executives and technology teams on material decisions, resolves cross-domain architecture issues, incorporates risk and resilience requirements, and guides federated execution. The role also mentors architects, supports architecture operating-model maturity, and may assist with major production incidents.

Own analytical integrity for a payments observability and AI platform. Responsibilities include analyzing transactional data, validating metrics and model behavior, back-testing anomaly detection and forecasting models, monitoring data and model drift, triaging analytical defects, creating executive-ready visualizations, and partnering with product and engineering teams on requirements and prioritization.

The Enterprise Architect will design scalable AI solutions, mentor teams, support business development, and manage client relationships while evolving technology practices.

Leads development of cloud-native, microservices-based applications and agentic AI systems. Designs resilient AWS architectures, manages Terraform infrastructure, builds multi-agent workflows, and promotes secure AI-assisted engineering practices. Troubleshoots recurring issues, drives automation, supports zero-downtime releases, and leads engineering communities of practice. The role also includes mentoring, stakeholder collaboration, agile delivery, and applying responsible AI, security, resiliency, and validation standards.

Lead software engineers and applied AI/ML practitioners while developing secure, scalable production systems in Java or Python. Integrate LLMs, generative AI, NLP, RAG, and coding assistants into software engineering workflows. Establish responsible AI governance, validation standards, testing, security, and operational practices. Guide system architecture, experiments, algorithm implementation, productionization, code quality, automation adoption, and technical decision-making across global teams.

Lead design, build, and operate AI-driven automation and infrastructure tooling. Develop secure production code, deploy on Kubernetes, define observability/SLOs, drive AI-assisted engineering adoption, and lead cross-team technical decisions.

Drive AI/ML solution sales for cable, media, and entertainment clients by developing POCs, proposing solutions, advising customers, building roadmaps, coordinating offshore delivery teams, and performing data-driven analysis to identify business improvements and implementation plans.

Leads software engineering and quality engineering for JPMorganChase’s Payments team. Builds and maintains large-scale test automation frameworks, integrates automated testing into CI/CD pipelines, and supports application development, system design, and operational stability. Drives responsible use of AI-assisted engineering tools, improves test quality and delivery speed, and establishes validation, security, and resiliency standards. Oversees complex, high-risk projects and promotes practices such as failure triage, contract testing, service validation, and canary testing.

Leads development of secure, scalable Java and AWS software systems, including microservices, event-driven platforms, and production machine-learning systems. Designs data and feature pipelines, model deployment and monitoring, automation, CI/CD, and operational stability practices. Guides code reviews, testing, secure coding, vendor evaluations, and responsible adoption of AI-assisted engineering tools. Collaborates across product, data, platform, SRE, and governance teams while promoting MLOps, LLM, observability, and model-monitoring practices.

Supports AI strategy and GenAI adoption across Payments Sales by translating sales priorities into product requirements, technology initiatives, and actionable insights. Partners with sales, data, product, platform, CRM, and analytics teams to deliver AI-enabled use cases, improve sales lifecycle efficiency, and enhance pipeline visibility. Contributes to voice-of-sales activities, use-case prioritization, governance, stakeholder alignment, training, enablement, and monitoring of emerging AI trends.

Lead SRE for AI platforms responsible for driving reliability culture, designing resilient systems, leading incident response, mentoring engineers, establishing SLOs/error budgets, applying AI-assisted operational workflows, and improving observability, CI/CD, container orchestration, and automation across services.

Supports AI, machine learning, and generative AI product initiatives for travel products. Responsibilities include identifying opportunities, developing requirements and user stories, coordinating cross-functional delivery, tracking projects with Agile tools, analyzing product metrics, conducting user and market research, and communicating AI-driven product impacts to stakeholders.

Lead end-to-end delivery of custom technology solutions across supply chain functions (planning, manufacturing, warehouse, logistics, merchandising). Define architectures and roadmaps, identify agentic AI use cases, guide development/testing/deployment, lead cross-functional teams, manage scope/timelines/budgets, and run client workshops to translate technical solutions into business outcomes.

Manage full sales cycle for enterprise accounts in the NYC/Mid-Atlantic region: hunt new logos, grow existing install base, build pipelines, meet quota, coordinate with BDR, marketing, and solutions architects, develop territory plans, forecast sales, build channel partnerships, and articulate/Leverage AI and cloud networking/security solutions to executive and technical stakeholders.