Artificial Intelligence Jobs in Jersey City, NJ

Lead Guidewire technology consulting and implementation workstreams for insurance clients across policy, billing, and claims. Manage project scope, timelines, budgets, risks, and deliverables while directing configuration, integration, testing, and deployment. Review technical designs and code, translate business needs into Guidewire recommendations, analyze transformation opportunities, and coach developers. Support cloud, data, analytics, and AI-enabled delivery modernization while maintaining technical standards and client relationships.

Design, customize, test, and troubleshoot Guidewire applications supporting insurance policy, claims, and billing workflows. Develop AI-enabled solutions, integrations, and automation; translate client requirements into technical solutions; interpret system data; and contribute to digital transformation engagements. The role also involves managing workstreams, reviewing junior team members’ work, guiding technical problem solving, and building client relationships while supporting Guidewire platform modernization.

Leads healthcare payer data science and modernization initiatives, developing predictive models, statistical analyses, and scenario-based insights from claims, reimbursement, utilization, and member experience data. Directs multiple analytical workstreams, advises executive clients, guides cross-functional teams, supports transformation roadmaps, and promotes responsible AI use. The role also shapes thought leadership, business growth, operational improvement, and delivery quality across payer advisory engagements.

Leads ServiceNow deployment workstreams for enterprise clients, managing implementation planning, budgeting, execution, risks, dependencies, and closeout. Oversees modules including ITSM, ITAM, ITOM, CSM, HRSD, SPM, NowAssist, and App Engine. Translates business needs into workflow automation, reviews deliverables, communicates with stakeholders, and coaches team members on ServiceNow architecture, configuration, and delivery methods.

Design and deploy AI systems and machine learning models, perform data wrangling and analysis, and integrate solutions into data infrastructure. Develop scalable AI applications, relational data systems, evaluation tools, automated tests, and monitoring capabilities. Assess AI behavior, robustness, bias, explainability, drift, hallucinations, and guardrails while evaluating technical controls and communicating findings to clients and stakeholders.

Leads enterprise PCI DSS assessments and regulatory compliance activities within JPMorganChase’s Cybersecurity Technology Controls team. Manages concurrent assessments, validates scope and documentation, coordinates with Qualified Security Assessors and control owners, identifies compliance gaps, guides remediation and compensating controls, and reports risk findings and metrics to stakeholders. Applies technology risk, audit, regulatory, and control expertise while using automation and artificial intelligence to improve assessment efficiency and quality.

Develop and deploy data solutions using Palantir Foundry and AIP for client engagements. Lead technical teams, coach team members, analyze system interactions, build applications with large datasets, and apply data engineering and analytics to deliver client outcomes. The role also includes managing client relationships, planning and executing projects, encouraging technology adoption, resolving stakeholder conflicts, and driving continuous improvement.

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Leads enterprise data and AI governance across policies, controls, risk management, compliance, privacy, cybersecurity, model risk, data quality, access management, and responsible AI. Partners with technology, legal, audit, risk, and business teams; oversees regulatory examinations and control remediation; presents governance metrics to executives; and builds a high-performing governance and AI policy team.

Leads technical account management and customer success for a firmwide data and AI platform. Owns onboarding, adoption, retention, expansion, customer health metrics, technical discovery, delivery planning, governance, escalations, and operational readiness. Partners with Product, Engineering, SRE, and support teams to translate customer requirements into executable plans, resolve blockers, improve reliability, and win new engagements. Coaches teams, establishes operating cadences, and communicates decisions and outcomes to senior stakeholders.

Advise Technology stakeholders on data ownership, governance, risk, and management practices. Lead maturity assessments, strategic roadmaps, operating model improvements, metrics, executive reporting, and capability enhancement initiatives. Partner with senior leaders across Technology, Risk, Controls, and CDAO to improve data quality, metadata, regulatory alignment, and governance effectiveness. Identify opportunities to apply AI, automation, and modern data platforms to scale data management outcomes.

Leads strategic enterprise account growth across retail, insurance, manufacturing, and hospitality customers. Builds executive relationships, develops account business plans, identifies and closes complex technology deals, and positions networking, hybrid cloud, AI, compute, storage, and services solutions. Leads cross-functional and partner teams, manages pipelines, drives customer satisfaction, and advises executives on digital transformation and IT strategy.

Leads multidisciplinary teams delivering AI-enabled, cloud-native applications on AWS. Oversees architecture, development, testing, deployment, modernization, platform engineering, security, reliability, and client advisory activities. Translates business objectives into technical roadmaps, guides complex engineering work, coordinates cross-functional architecture reviews, communicates delivery risks and options, and coaches teams across multiple workstreams.

Leads contact center transformation strategy engagements, including operating model assessments, business analysis, roadmap development, stakeholder facilitation, and implementation planning. Manages client accounts and project teams, coaches junior staff, evaluates customer behavior and market trends, and develops recommendations addressing service performance, profitability, competitive positioning, digital tooling, AI-enabled processes, and customer strategy.

Support strategy consulting engagements focused on contact center transformation. Analyze operating models, workflows, customer insights, market trends, and data to develop practical recommendations. Manage workstreams, create client-ready deliverables, present findings, review team outputs, coordinate tasks, resolve issues, and mentor junior staff. Apply business analysis, process improvement, AI fluency, and digital tools to support service redesign and implementation planning while building client relationships.

Leads third-party technology risk assessments and control improvements across corporate applications. Evaluates vendor risks, contract deviations, residual risks, and control effectiveness; partners with product teams, vendors, security, governance, and business control stakeholders. Delivers risk metrics and executive reporting, recommends remediation strategies, and ensures alignment with regulatory and industry standards. Uses authorized AI tools to synthesize evidence and prepare reporting while validating outputs for security, auditability, and regulatory compliance.

Leads technology risk and control activities across an application portfolio. Responsibilities include identifying and mitigating operational and compliance risks, evaluating control effectiveness, managing issues, conducting root cause analysis, reporting risk insights, and supporting regulatory compliance. The role also applies enterprise AI and machine learning governance, validates AI-assisted outputs, protects sensitive data, and advises technology leaders and senior management on risk posture and remediation strategies.

Leads client portfolios using ZAIDYN data management and analytics solutions for emerging pharmaceutical companies. Responsibilities include business development, solution design, technology implementation, project and staffing management, client presentations, global team leadership, technical escalation, and mentoring. The role oversees scalable deployments involving analytics, AI, cloud, big data, BI, data governance, integration, and master data management.

Leads financial statement audits for digital assets and financial services clients, evaluating regulatory compliance, governance, risk management, and internal controls. Applies advanced auditing and technical accounting expertise to identify material misstatements and issue audit reports. Directs complex engagements, coaches diverse teams, manages client relationships, communicates findings, and reinforces professional, independence, and ethical standards. The role also involves data analysis and exploring AI and machine learning platforms to improve processes.

Leads enterprise AI product management transformation for infrastructure platforms. Owns product strategy, roadmaps, lifecycle execution, performance, risk, and growth. Establishes a product management Center of Excellence, develops standards and governance, coaches product managers, and drives organizational adoption. Oversees AI assistants and workflow automation across the product lifecycle, including governance, cost controls, and value measurement. Partners across engineering, architecture, strategy, risk, and business teams to embed regulatory alignment and improve product management maturity.

Provides analytics consulting to help clients translate complex data into business decisions. Develops statistical frameworks, guides analytical approaches, interprets findings, creates strategic recommendations, and communicates insights through presentations and deliverables. Partners with clients and cross-functional teams, manages project updates, mentors junior analysts, and supports solution implementation. Requires strong quantitative, communication, client-facing, and problem-solving skills, with interest in analytics, AI, and business strategy.

Leads ITSM Problem Management for production technology services, driving root cause analysis, incident recurrence prevention, service resilience, operational readiness, and process improvements. Collaborates with engineering, development, and support teams; manages ServiceNow problem tickets and defects; supports audits and regulatory compliance; and presents operational, risk, and service metrics to senior stakeholders. Uses Python, AI, and data analysis to automate problem management and improve decision-making.

Lead the development and production deployment of generative AI, agentic AI, and machine learning solutions in Python. Establish enterprise semantic modeling, ontology, and unified semantic layer standards; build AI pipelines, evaluation frameworks, intelligent workflows, and MLOps capabilities. Implement responsible AI governance for regulated environments, partner with business and technical stakeholders, and mentor engineers and data scientists while influencing enterprise technical direction.

Leads the end-to-end lifecycle of data and AI governance products, from discovery and roadmap development through delivery, adoption, and value measurement. Owns prioritization, backlog management, stakeholder alignment, governance-by-design controls, auditability, documentation, and risk reduction. Partners with product, engineering, data science, legal, and risk teams to automate and standardize governance processes, communicate complex topics to senior leaders, and manage delivery health across concurrent initiatives.