Artificial Intelligence Jobs in Jersey City, NJ

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.

The AI Engineer will develop agentic AI systems for production environments, collaborating with production teams to optimize reliability and costs, while addressing runtime challenges and building machine learning operations.

The Principal AI/Machine Learning Engineer will lead the adoption of AI/ML in manufacturing by defining use cases, driving implementation, and ensuring organizational readiness.

The Senior FP&A Analyst manages financial planning and reporting, conducts variance analysis, develops financial models, identifies risks, and leads budgeting processes while collaborating with various departments.

Lead AI Engineer to architect, develop, deploy, and support enterprise-scale agentic AI solutions using LLMs, RAG, model orchestration and secure APIs. Ensures security, governance, and compliance, collaborates cross-functionally, evaluates emerging technologies, contributes to AI roadmap, and mentors junior engineers to drive automation, efficiency, and improved customer experience.

Design, build, and operationalize enterprise-grade AI agents and an orchestration layer. Implement agent patterns, state management, observability, and governance. Integrate Azure/Azure AI services, support production-grade deployments, perform model/prompt updates, and provide technical leadership to scale reusable agent frameworks across the organization.

Lead content strategy and AI-enabled content transformation for Consumer line of business. Define AI-driven content frameworks, partner across digital, SEO, analytics and product teams, modernize content planning/creation/measurement, and operationalize scalable playbooks to improve engagement and business outcomes while managing stakeholders and budgets in a matrixed, regulated environment.

Lead architecture and execution of an enterprise AI platform on Azure: define multi-year roadmap, model lifecycle and evaluation standards, drive multi-LLM orchestration, enforce governance and compliance, build monitoring/observability and cost-optimization, manage identity and security controls, and enable firmwide adoption and executive reporting across Tax, Audit, Advisory, and Outsourcing.

The role involves developing governance frameworks for Microsoft Copilot and Power Platform, ensuring security and compliance, and training citizen developers while monitoring operational governance across multiple regions.

The role involves enabling enterprise-wide adoption of Microsoft AI and Automation tools, developing scalable platforms, and ensuring compliance with regulations. Responsibilities include platform strategy, architecture, agent development, and governance in a highly regulated financial environment.

Senior AI leader responsible for defining enterprise AI strategy, prioritizing high‑value use cases across underwriting, pricing, claims and operations, building an AI organization, partnering with technology/data/risk teams, ensuring regulatory compliance, and driving adoption and measurable business outcomes.

Lead and grow the mobile and AI platform engineering team to deliver reliable, real-time DNA-based health insights. Own roadmap, delivery predictability, React Native releases, performance, production reliability, AI model orchestration, multi-agent systems, incident response, API contracts, and cross-functional partnerships to ensure scalable, trustworthy AI experiences.

Partner with the CEO/COO to translate strategy into execution, build AI-enabled operating systems, drive cross-functional programs, run OKRs and planning cadences, scale vendor/procurement, and lead high-priority projects end-to-end.

Own the long-term vision, roadmap, and execution of Sequencing's AI platform to turn genomic data into conversational, personalized health guidance. Lead AI-native product strategy, evaluate and productize emerging models and agents, partner with engineering and bioinformatics, run experiments and analytics, and optimize engagement, retention, and trust for mobile and web experiences.

Lead and scale the product organization for AI-powered clinical documentation. Define product vision and roadmap, drive market/customer discovery, own end-to-end product delivery, set generative AI/LLM strategy, partner with engineering and cross-functional teams, and report product KPIs to executives.

Lead development and scaling of AI-powered clinical applications using LLMs. Own feature lifecycle from discovery through delivery, partner with engineering and QA, perform user research, design generative AI capabilities, and prioritize roadmaps to streamline pharmaceutical workflows.

The Tech Lead will design and develop Python-based backend services for NLP and chatbots, support cloud-native technology transformation, and collaborate with stakeholders.

Lead design and evolution of scalable, secure enterprise data and AI architectures across platforms. Define integration patterns, semantic models, knowledge graphs, metadata and governance, and enable AI use cases (RAG, semantic search). Partner with engineering, cloud, and governance teams to create reusable architecture templates, standards, and deliver hands-on guidance to delivery teams.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Build and maintain production-grade React+TypeScript web interfaces for data-intensive, real-time AI products. Own end-to-end frontend features, optimize UI performance for large datasets, collaborate with design and backend teams, establish frontend best practices, improve architecture and tooling, and resolve production issues across browsers and devices.

The Senior Software Engineer will lead the development of AI solutions for the life insurance sector, overseeing full stack application design and delivery while guiding junior engineers.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

The AI Engineer will build AI-powered applications, prototype solutions, implement workflows using LLMs, and manage sub-projects while improving internal tools.

Lead AI and data transformation initiatives, develop AI strategies, deliver AI/ML solutions, mentor teams, and drive innovation for enterprise clients.

Lead growth strategy and execution for UpToDate Expert AI across awareness, acquisition, activation, and early engagement. Drive cross-functional initiatives with marketing, sales, engineering, and data teams to improve discovery, onboarding, and activation. Define OKRs, measurement frameworks, run experiments, and translate clinician insights into product and go-to-market actions while balancing clinical, privacy, and regulatory constraints.