Artificial Intelligence Jobs in Jersey City, NJ

Design and implement full-stack applications and AI agents to enable rapid development and deployment of AI solutions in critical industries. Mentor engineers and take ownership of projects while applying secure SDLC practices and collaborating with cross-functional teams.

Design and implement full-stack applications and AI agents for the GenAI platform, ensuring rapid development and deployment across critical industries. Collaborate with teams to deliver secure and reliable cloud-native systems.

This role involves designing and building next-gen payments platforms using blockchain and AI technologies, focusing on payment modernization, security, and regulatory compliance.

Lead always-on, multi-channel B2B demand generation programs targeting new logos and verticals for AI and data solutions. Build full-funnel campaign architecture, define ICPs, drive MQLs, align with sales on MQL criteria, manage pipeline coverage models, deploy localized messaging, and report on pipeline influence and channel ROI using marketing and analytics tools.

Lead product marketing and customer insights for Wiley's AI and data analytics portfolio. Build positioning, GTM strategy, pricing guidance, sales enablement, VoC programs, win/loss analysis, market sizing, and competitive intelligence. Build and lead a cross-functional team to turn market insight into commercial outcomes and drive enterprise sales in R&D-intensive verticals.

Design, build, and optimize generative AI, RAG, and agentic RAG systems for drafting, search, and reasoning. Improve LLM outputs via prompt design, retrieval optimization, embeddings, reranking, and evaluation. Develop production-grade ML components and retrieval pipelines using OpenSearch/Solr, write maintainable Python code, and collaborate with engineering, product, and domain teams to improve relevance, accuracy, and user trust.

Hunter-focused enterprise sales role to build net-new pipeline and close Agentic AI, cloud, and identity security services. Own full sales cycle, prospect into CIO/CISO/CTO-level buyers, collaborate with architects, maintain Salesforce hygiene, and shape GTM strategy in a small startup environment.

Lead AI and sales automation product efforts for Salesforce: translate business needs into Jira stories, design automations and integrations, coordinate UAT, consolidate data sources, and build AI-driven solutions to reduce manual CRM administration. Occasional hands-on scripting for simple automations.

Lead hands-on AI development and deployment to automate Salesforce administration and improve sales effectiveness. Build, evaluate, and deploy LLM-based use cases (Gemini, Agentforce), integrate multi-source data securely, collaborate with Salesforce IT and cross-functional teams, and measure success by reduced manual administrative effort and successful AI deployments.

Lead firmwide AI enablement by setting strategy and roadmap, designing multi-level training, running an AI champion community, producing adoption analytics, shaping governance, evaluating tools and vendors, and managing stakeholders and a small team to drive responsible AI adoption and measurable business impact.

The AI Risk Manager safeguards AI solutions by managing risks, ensuring compliance with regulations, and developing risk mitigation plans, collaborating with stakeholders.

As a Senior AI Engineer, you will design and implement AI solutions, collaborate with teams to define success metrics, and iterate on AI model performance.

The Principal TRI AI Governance Specialist manages DTCC's AI governance framework, ensuring compliance and risk management while promoting responsible AI use across the organization.

Lead the development of an intelligent document processing platform using Generative AI, managing a high-performing engineering team, and driving technical innovation.

Lead polyglot engineering to design, build, and scale end-to-end systems across backend, frontend, data, and infrastructure. Prototype and productionize multi-language solutions, architect microservices and distributed systems, promote CI/CD, security, and performance best practices, and mentor engineers to drive platform reuse and enterprise agility.

The role involves leading the design and delivery of multi-agent systems for underwriting and claims automation, ensuring production readiness and business alignment.

The AI Sales Specialist will develop sales strategies, engage clients, manage relationships, negotiate contracts, and provide insights on AI technologies to drive business value for enterprise clients.

The Senior Solution Owner will lead product strategy and execution for AI and data solutions, overseeing product lifecycles and data migration initiatives, and ensuring effective cross-functional collaboration.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Lead the delivery of enterprise data solutions on the Databricks Lakehouse platform, coordinating teams and ensuring high-quality data pipelines and analytics solutions.

The role involves leading change management initiatives, developing strategies for organizational transformation, and ensuring adoption of new technologies and processes across the enterprise.

Lead AI engineering efforts in banking, focusing on AI solutions, team management, data strategy, governance, and driving AI integration in workflows.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

Lead design, architecture, and production deployment of GenAI and agentic AI systems. Build Python backend services, secure APIs, conversational AI, and scalable data pipelines. Drive model fine-tuning, optimization, CI/CD, containerized deployments, and mentor engineering teams while ensuring compliance, security, and operational resilience.

Lead design, development, deployment, and maintenance of large-scale Python-based generative AI platforms and services. Collaborate with data science, technical, and business stakeholders to define architecture, deliver production APIs, enforce Python standards and testing, drive CI/CD and monitoring, mentor developers, manage vendor partnerships, and ensure governance, risk, and controls alignment for enterprise GenAI solutions.