Artificial Intelligence Jobs in Jersey City, NJ

Lead client consulting workstreams focused on demand, supply, inventory, production, capacity planning, forecasting, and S&OP. Assess planning processes, design improvements, support APS and ERP implementations, develop analytics and AI-enabled planning solutions, and manage client relationships, deliverables, timelines, and junior team members. The role requires hands-on supply chain planning experience and collaboration with cross-functional stakeholders.

Leads technical account management and customer success for a firmwide data and AI platform. Owns customer engagement, onboarding, adoption, retention, delivery plans, governance, technical discovery, escalations, operational readiness, and expansion opportunities. Partners with Product, Engineering, SRE, and operations teams to translate requirements into production-ready solutions, drive cross-functional execution, improve customer health metrics, and establish scalable success practices across complex internal customer organizations.

Lead the research, architecture, and production delivery of agentic and generative AI solutions for complex banking operations. Design collaborating agents, reusable services, evaluation frameworks, and distributed machine learning systems. Establish experimentation, monitoring, safety, reliability, and governance practices while partnering with business, product, and engineering teams. Mentor engineers and researchers and drive technical alignment across stakeholders.

Leads post-trade operations for Fixed Income and Equities, overseeing clearance, balancing, trade matching, settlement, reconciliation, break management, controls, and risk escalation. Drives root-cause analysis, automation, process improvements, KPI and SLA governance, audit readiness, and regulatory compliance. Partners cross-functionally with Trading, Technology, Product, Risk, and Operations teams while managing strategic initiatives, communicating with senior stakeholders, coaching teams, and fostering operational excellence.

Supports client assurance engagements involving data analytics, ERP integration, IT controls, business process improvement, and regulatory compliance. The associate interprets data, contributes to audit and assurance services, develops technology skills, and collaborates with senior staff to deliver objective assessments and tailored client solutions. The role is designed for students or recent graduates in accounting, information systems, analytics, business, or technology disciplines.

Own the roadmap and execution for W&B Models, an experiment-tracking platform for AI researchers. Improve experiment organization, training visualization, monitoring, evaluations, and large-scale analysis across web and mobile. Conduct user research, translate ML workflows into product decisions, collaborate with engineering and design, and use data and feedback to launch polished, high-performing experiences. The role requires deep familiarity with ML research, technical product management, data visualization, AI tools, and developer or researcher audiences.

Own and continuously improve technology portfolio governance across multiple lines of business. Manage governance calendars, stakeholder roles, investment taxonomies, data quality, reporting standards, resource utilization views, escalations, and executive communications. Translate complex portfolio information into actionable narratives and investment decisions while reducing ad hoc reporting. Build governance routines, knowledge bases, forums, and training, partnering with senior leaders across Finance, Business Management, and technology stakeholders.

Leads data governance and ownership initiatives, defining data requirements, quality standards, metadata, lineage, controls, and curated datasets. Performs SQL-based testing, validation, reconciliation, and root-cause analysis. Partners with technology and business teams to mitigate data risk, support analytics and machine learning use cases, and improve data products. Applies AI and LLM tools to automate governance activities and contributes to roadmap, agile delivery, and stakeholder management.

Leads enterprise data ownership across Liquidity & Account Solutions, establishing governance frameworks, quality standards, metadata management, lineage, access controls, and risk remediation. Partners with business, technology, architecture, and data teams to improve data discoverability, reuse, interoperability, analytics, and AI readiness. The role also leads governance forums, supports regulatory adherence, and builds high-performing data management teams.

Defines technical target states and architecture strategies for blockchain products, partnering with engineering teams and stakeholders. Designs, develops, tests, troubleshoots, and reviews secure production software. Evaluates emerging technologies, vendors, and AI-enabled capabilities while ensuring resiliency, auditability, security, and sensitive-data controls. Requires hands-on experience with Ethereum, Solidity, EVM, Solana, smart contracts, token standards, blockchain tooling, and on-chain/off-chain integrations.

Lead site reliability for liquidity risk applications, owning non-functional requirements. Drive resiliency, security, scalability, monitoring, automation, and enterprise-authorized AI adoption for reliability workflows. Influence strategy, run blameless post-mortems, coach engineers, hire and develop talent, and ensure traceability, auditability, and cross-team collaboration.

Lead data science and AI initiatives for Home Lending Operations by developing product analytics, machine learning, experimentation, KPI, and trigger-driven capabilities. Translate ambiguous business problems into actionable insights, improve client journeys and operational efficiency, and identify scalable agentic AI use cases. Partner with product, strategy, operations, and technology teams while communicating recommendations to senior stakeholders in a regulated environment.

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

Leads Inato’s marketing organization and strategy, including account-based marketing for enterprise sponsors, integrated sales campaigns, product positioning, go-to-market execution, customer marketing, and advocacy programs. Establishes marketing goals and metrics tied to business outcomes while partnering with Sales, Product, Customer Success, Strategy, and executive leadership. Coaches and develops the marketing team, builds internal product marketing capabilities, and drives measurable pipeline creation, customer expansion, and market differentiation.

Leads enterprise data-domain architecture strategy across products, applications, and technologies. Establishes governance, reusable frameworks, architectural standards, and portfolio guardrails while evaluating emerging technologies and AI capabilities. Advises leadership on target-state architecture, promotes hybrid and multi-cloud adoption, reduces tooling duplication, and improves traceability, resilience, security, cost performance, and operational governance. Requires deep expertise in data management architecture, databases, ETL, data platforms, analytics, mining, and data governance, along with extensive cloud-native experience.

Lead cross-functional technology programs by building integrated plans, tracking dependencies and risks, running governance forums, managing resources and decisions, producing executive-ready communications, and applying AI-assisted analysis with strong validation and data-handling practices.

Lead and contribute to full-stack Java/React development, design secure high-quality production code, drive adoption of AI-assisted engineering, improve automation and operational stability, evaluate vendor architectures, and lead engineering communities of practice while promoting resilient, secure CI/CD practices.

Lead cybersecurity architecture for cloud-native enterprise solutions: evaluate controls and new technologies, advise stakeholders, provide technical guidance, promote firmwide SDLC practices, and mentor peers to mitigate risk and adopt strategic solutions.

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 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 transformation of strategic plans into programs and projects across business units. Oversee execution, risk mitigation, and data-driven progress monitoring. Build and lead teams, engage stakeholders, resolve conflicts, and ensure alignment with business strategy.

Lead firmwide technology strategy for Data & AI, build partnerships with cloud and infrastructure vendors and the venture ecosystem, drive innovation adoption, evaluate and scale new technologies, raise internal awareness of Data & AI opportunities, support client-facing business development and strategic investments, and influence senior stakeholders to align partner roadmaps with JPMC objectives.

Lead delivery of complex technology programs for Asset & Wealth Management by defining strategy, scoping problems, advising senior stakeholders, managing cross-functional teams, driving roadmaps, and delivering executive-level communications while mentoring junior staff and managing risks and resources.

Builds, scales, and maintains machine learning platforms supporting model training, deployment, monitoring, and lifecycle management. Develops secure platform services, APIs, automation, and CI/CD pipelines while integrating data engineering and feature management capabilities. Ensures reliability, scalability, and performance, produces architecture documentation, collaborates with data scientists and product teams, and promotes AI-assisted engineering practices and standardized validation across the team.

Lead firmwide data management and governance strategy to make data AI-ready. Define vision, prioritize initiatives (data products, metadata, publishing), perform analysis and industry research, create executive presentations, influence senior stakeholders, and coach junior team members.