Artificial Intelligence Jobs in Newark, NJ

Build and maintain AI-powered go-to-market systems that automate sales, expansion, marketing, forecasting, handoffs, and post-sales workflows. Optimize processes, maintain CRM data quality, test and monitor automations, connect GTM tools, and translate operational needs into scalable technical solutions. The role uses AI and iPaaS tools to surface next-best actions, improve deal velocity, and support customer lifecycle operations.

Lead global commercial and operational initiatives to accelerate Private AI adoption. Establish governance and operating rhythms, run monthly business reviews, prioritize accounts and use cases, define strategic metrics, align ecosystem and commercial strategies, and build business cases and growth models to guide executive decision-making.

Lead enterprise sales efforts for Life Sciences customers by identifying opportunities, building executive relationships, developing strategic sales plans, managing pipelines and forecasts, and delivering technical solutions. Collaborate with engineers, architects, consultants, and partners to address customer needs across AI, cloud, infrastructure, cybersecurity, and digital strategy. Serve as the primary customer contact, lead sales meetings, and manage a cross-functional team. Travel up to 25% is required.

Lead quantitative equity research initiatives, develop security-selection signals, integrate complex datasets, and enhance investment processes. Author research publications, monitor academic and sell-side research, present findings to clients and prospects, and drive innovation in quantitative investing. The role requires deep asset-pricing knowledge, advanced analytical skills, Python proficiency, and the ability to communicate complex investment concepts effectively.

Owns the prioritized backlog and day-to-day delivery for an Agile scrum team supporting Bank of America’s enterprise Document AI program. Translates business objectives into user stories and acceptance criteria, prioritizes scope, accepts completed work, manages stakeholders, removes ambiguity, and supports scalable AI capability adoption while ensuring quality, regulatory alignment, and delivery commitments.

Leads AI and policy governance, business controls, risk oversight, and quality assurance within a financial-services enterprise. Responsibilities include managing AI opportunity pipelines, coordinating risk assessments and approvals, monitoring and testing controls, overseeing remediation, developing governance routines and reporting, supporting audits and regulatory exams, and advising senior stakeholders on operational risk, compliance, and responsible AI adoption.

Drive net-new enterprise revenue for WRITER’s AI agent platform by managing the full sales cycle, prospecting strategic accounts, developing opportunities, leading executive discussions, negotiating deals, and maintaining accurate pipeline forecasts. Partner with product and customer success teams on tailored solutions and deployments while serving as a trusted product expert. The role targets global enterprises with 8,000+ employees and requires consultative, outbound, quota-carrying SaaS sales expertise.

Leads the operating model for enterprise data products, including governance, development, certification, publishing, application health, access controls, quality, and compliance. Designs scalable processes for data platforms such as Starburst, coordinates service providers, monitors infrastructure performance, manages vulnerabilities and upgrades, performs control testing, supports audits, and drives issue remediation and continuous improvement. Partners with executives and technical teams to align operational, risk, security, and governance strategies with enterprise objectives.

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.

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.

Designs and drives complex Data and AI solutions for enterprise clients, including cloud data architectures, pipelines, warehousing, governance, security, BI, AI/ML, and generative AI systems. Engages senior executives, supports sales and RFP responses, delivers technical presentations and demonstrations, develops proofs of concept, evaluates technology strategies, and mentors solution personnel. The role requires extensive data and analytics experience, pre-sales architecture expertise, strong communication skills, and the ability to travel up to 50%.

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 Prudential’s enterprise AI workforce transformation strategy, including AI-enabled job redesign, human-AI teaming, organizational models, governance, talent architecture, career paths, change management, and global workforce planning. Partners with technology and people executives to guide agentic AI adoption, develop frameworks and playbooks, oversee responsible AI practices, measure productivity and ROI, and build organizational capabilities for AI-augmented work across multiple geographies.

Lead the hands-on architecture and development of greenfield digital products and the engineering platform supporting them. Own frontend, backend, cloud infrastructure, CI/CD, Kubernetes, infrastructure as code, observability, reusable services, and developer tooling. Establish scalable engineering practices, automate delivery, mentor engineers, and partner with product and design teams to build customer-focused solutions. The role requires deep full-stack, distributed systems, cloud, platform, and SRE expertise in a highly autonomous environment.

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.

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.

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.