Artificial Intelligence Jobs in Newark, NJ

Leads enterprise analytics transformation by managing integrated plans, milestones, resources, dependencies, risks, governance, executive reporting, and stakeholder decisions. Partners across business, technology, data, product, controls, and change teams to deliver certified data products and AI capabilities. Drives communications, training, onboarding, adoption, operating-model improvements, and alignment of investments to enterprise priorities.

Supports analysis of business processes, data flows, operational controls, and data quality to identify risks, inefficiencies, and improvement opportunities. Partners with business, risk, finance, operations, technology, and audit stakeholders on process reviews, issue resolution, reporting, and continuous improvement. Uses SQL, analytics, automation, AI-enabled tools, dashboards, and visualizations to generate insights and communicate recommendations.

Develops and validates wholesale credit risk, market risk, stress testing, loss forecasting, scorecard, and regulatory capital models. Performs statistical analysis on large datasets, prepares technical documentation and white papers, supports model risk management, and implements models in production environments. Collaborates with technology teams, stakeholders, and senior management to address findings, monitor model performance, improve processes, and communicate quantitative results.

Owns the roadmap, strategy, risk management, and continuous improvement of data platforms supporting financial-crime analytics, detection models, investigations, and AML operations. Responsibilities include requirements gathering, backlog prioritization, agile delivery, data analysis, model lifecycle management, monitoring, issue remediation, governance, and stakeholder communication across business and technology teams.

Partners with senior leaders on workforce planning, talent management, succession, organizational effectiveness, employee relations, and leadership development. Leads HR transformation through process redesign, automation, analytics, AI-enabled tools, and change management. Develops workforce dashboards, guides data-driven talent decisions, improves employee experience, ensures HR compliance, and coaches leaders through organizational change and performance matters.

Leads organization-wide architecture for AI-native applications, defining standards and reference implementations for backend systems, data platforms, APIs, microservices, LLM integrations, retrieval-augmented generation, and agentic workflows. Designs scalable cloud and on-premises architectures, ensures healthcare security and compliance, conducts architecture reviews, partners with technical and business leaders, and mentors senior engineers while remaining hands-on in code.

Build prototypes and utility tools using GenAI and open-source LLMs, evaluate low-code and no-code automation platforms, and identify business-process automation opportunities. Translate business needs into technical requirements and user stories, support AI-enabled workflows, train internal teams, and document tools and processes. The role bridges business and technical teams while improving operational efficiency across Medscape Education.

Design, build, and deploy production-grade AI applications end to end. Develop stateful multi-agent workflows with LangGraph, rapidly prototype full-stack applications, and create automated LLM evaluation systems measuring accuracy, latency, hallucinations, and regressions. Integrate AI safely into business workflows, work with vector and relational databases, provide framework feedback, and mentor teammates while owning applications from concept through production.

Own the strategy, discovery, prototyping, productization, and scaling of AI-powered commercial offerings. Develop supporter-facing workflows, content customization, reporting, analytics, and campaign performance capabilities. Partner with sales, marketing, clients, platform product, AI/ML, engineering, and data science teams to create scalable and monetizable products. Track adoption, revenue contribution, efficiency gains, and AI feature impact while ensuring responsible, reusable platform capabilities.

Develop and deploy AI-powered internal and client-facing solutions using generative and agentic AI. Assist with design documentation, prompt engineering, LLM integrations, testing, troubleshooting, deployment, monitoring, and production support. Collaborate across teams while learning DevOps practices and contributing to organization-wide AI automation initiatives.

Leads AI product strategy and MarTech enablement for marketing, from use-case prioritization and product development through production deployment, adoption, support, and ROI measurement. Oversees AI decisioning, orchestration, prompt engineering, responsible AI, and MarTech platforms while partnering with data, technology, privacy, legal, and agile delivery teams. Builds and mentors a multidisciplinary team, manages vendors, translates technical concepts for executives, and drives reliable PI planning and value realization across a matrixed organization.

Lead hands-on design and delivery of production-grade AI solutions within a vertical. Architect LLM and agentic systems, cloud and data platforms, run technical deep-dives, advise executives, support pre-sales, and build reusable reference architectures and domain-specific accelerators to scale engagements and practice growth.