Artificial Intelligence Jobs in Jersey City, NJ

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.

Hunter-oriented BDM responsible for sourcing and qualifying new enterprise and mid-market opportunities across North America, building pipelines, outbound prospecting, coordinating discovery, partnering with leadership to close deals, and attending events (travel ~40%). Focus on selling consulting and technology services.

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 Gen AI and data science strategy for Markets Operations Technology. Manage and mentor data science and ML teams, drive end-to-end development and production deployment of LLM/RAG solutions, collaborate with stakeholders, ensure regulatory and ethical compliance, promote engineering best practices (Agile, DevOps, CI/CD), and advance research and innovation in generative AI.

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.

Lead AI strategy and execution for marketing by discovering process value, building secure RAG and multi-agent solutions, developing deployable AI assets and SOPs, and enforcing governance across Google AI platforms to drive measurable marketing productivity and ROI.

Lead design and delivery of enterprise Generative AI solutions (LLM, RAG, vector search, Text-to-SQL). Ensure production readiness, model lifecycle management, security, compliance, and observability. Partner with product, data, cloud, risk, and DevOps teams, and mentor AI/data engineers.

The Senior Product Manager will define the product strategy and roadmap for AI and data products, lead product initiatives, and collaborate with engineering and data science teams. The role requires transforming complex problems into actionable products that enhance healthcare decision-making.

Lead development and execution of enGen and enterprise AI strategy, drive AI adoption and commercialization, manage and grow teams, ensure operational excellence and compliance, partner across the enterprise to deliver scalable cloud-based AI solutions, and generate new revenue streams through AI initiatives.

Lead end-to-end delivery of Voice AI projects: scope, plan, track, and hand off production. Align product to customer needs, set and monitor metrics, manage scope, resources, budgets, testing, and client communications while working closely with engineering and data teams.

The AI Engineer will analyze business processes for automation opportunities, design and maintain RPA solutions, and develop Intelligent Document Processing systems while collaborating with stakeholders and ensuring reliability of solutions.

Lead customer-facing, consultative upsell efforts for AI legal solutions at law firms: drive discovery, map workflows, design demos and POCs, influence stakeholders, and partner with sales/product to close and ensure adoption.

Build and ship AI-powered automations and agents across business teams. Contribute to OUTGPT platform, implement integrations (APIs, SQL, Snowflake, Salesforce), deploy to AWS, and collaborate with stakeholders while receiving and giving mentorship.

Own and grow OUTFRONT's internal AI platform and external agent infrastructure: move OUTGPT to production, evolve the Agency Connect MCP, design agent infrastructure (routing, guardrails, observability, secrets, cost controls), operationalize AWS AI stack, integrate with internal systems, and mentor the AI & Automation engineering pod.

The Principal Data Scientist will create scalable data solutions and machine learning models, collaborating with teams to drive innovation in the financial industry.

The AI Product Owner will lead the lifecycle of AI products, partnering with business stakeholders, translating needs into requirements, and ensuring successful implementation and adoption of AI solutions.

Lead development and scaling of a multi-tenant agentic AI platform, writing production code and guiding architecture. Build agent frameworks, RAG and vector/graph integrations, fine-tuning pipelines, and collaborate with SMEs and frontend teams to deploy agent-driven enterprise workflows.

Lead research, design, and deliver Pearson's scalable learner model and AI-driven features. Partner with product, engineering, and design to define data requirements, build prototypes, maintain data pipelines, ensure data quality, and translate research into production ML capabilities and business growth.

Develop, test, and maintain AI-powered applications using generative AI and LLMs; collaborate with cross-functional teams to implement AI solutions, analyze data to inform features, and optimize application performance.

Design and build AI-powered tools to accelerate incident detection, triage, root-cause analysis, and automation for Credit trading production. Partner with support, development, and AI teams to embed AI into workflows, maintain high availability, analyze logs/metrics, and measure reductions in MTTR and operational toil.

The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.