Top Artificial Intelligence Jobs

The program offers hands-on exposure to AI workflow automation and enterprise systems through project-based learning, mentor guidance, and team collaboration activities.

Design, build, and deploy scalable AI/ML models (especially NLP and predictive models), implement MLOps and data pipelines, optimize model performance, research prototypes, ensure ethical and compliant AI, and collaborate with product, engineering, and data teams to embed AI into the leave management platform.

Lead integration of AI and automation into global content and metadata workflows. Identify and prioritize opportunities, partner with cross-functional teams to design and deploy scalable AI solutions, oversee global implementation, report outcomes to leadership, and drive continuous improvement and governance across content operations.

Lead and develop a team of ~5 clinical AI individual contributors across two product pods. Own clinical AI roadmap, quality, and delivery while doing hands-on work (prompting, evaluation design, error analysis, clinical content). Provide technical and clinical guidance, coach execution and project planning, hire and interview candidates, and represent clinical perspective with product, engineering, and customers. Hybrid role based in San Francisco (3x/week).

As a Sales Development Representative, you will generate and qualify leads through inbound and outbound efforts, collaborating with Account Executives to drive sales growth.

Design and implement AI-powered automation systems, build scalable backend services, make architectural decisions, and collaborate with product and data teams.

Drive advanced modeling and analytics for fraud detection and identity theft. Lead technical initiatives and manage full model lifecycle.

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

As the AI Transformation Lead, you'll drive AI adoption across teams, build AI-powered workflows, and establish foundational systems and metrics for continuous improvement in operations.

Design, build, and operate production-grade agentic AI systems and LLM-powered features for financial workflows. Implement RAG pipelines, tool invocation, agent orchestration, vector storage, monitoring, and shared AI infrastructure while ensuring reliability, security, auditability, and regulatory compliance.

Lead the development of agentic AI systems at Amex Tech, guiding engineering teams, establishing technical direction, and influencing cross-team initiatives to enhance AI capabilities and improve customer interactions.

Lead research and prototype development for generative AI and emerging technologies. Design architectures, build prototypes and proofs-of-concept, evaluate external partners, and collaborate across teams to translate research into production-ready recommendations and solutions.

Lead a team to design, build, and deploy AI-powered product management tools and multi-agent systems. Implement MCP infrastructure, production observability, and scalable integrations with enterprise platforms. Drive adoption, governance, and AI-enabled operating models while partnering across Product, Engineering, Risk, and Governance to measure impact and ensure responsible use.

The Director of Data Engineering - Agentic AI will lead the strategy and execution of agentic AI systems, guiding architectural standards and managing high-performing teams, while influencing investment strategy and ensuring cross-team integration for cohesive solutions.

Lead design and delivery of Agentic AI IAM and secrets management across hybrid environments. Build secure authentication/authorization, centralized secrets vaulting, automated rotation, governance, monitoring, and operational metrics. Partner with infrastructure, cloud, DevOps, application, and risk teams to implement Zero Trust, machine identity security, and AI agent safeguards while driving enterprise program execution and compliance.

The AI Enablement Lead will design and conduct training programs to improve AI fluency within Juniper Square, focusing on tools like Claude and Cowork. Responsibilities include curriculum development, leading sessions, coaching, and measuring adoption outcomes.

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.

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.

Lead strategy and roadmap for membership personalization platform integrations and agentic capabilities. Define APIs, adapters, and reusable services, partner with engineering and data science, drive GenAI/agentic use cases, set product metrics and adoption goals, and communicate priorities and outcomes to senior stakeholders while balancing short-term delivery with long-term scalability and reliability.

Lead strategy and roadmap for AI platform tools, integrations, APIs, gateways, and agentic capabilities. Partner with engineering, data science, and partners to build reusable services, drive GenAI/agentic use cases, define metrics, and balance short-term delivery with long-term scalability and adoption across Amex's digital ecosystem.

Lead global commercial strategy and execution for AI infrastructure sales across data center, edge, and industrial markets. Own revenue targets, build strategic partnerships with hyperscalers/OEMs, lead complex deals, scale a global sales organization, and align cross-functional teams on product roadmaps, supply chain, and market expansion.

Lead design, development, and deployment of advanced AI/ML models and LLM solutions. Mentor and manage small teams, set data science strategy and governance, collaborate with product and cross-functional stakeholders, analyze large datasets, and drive best practices in model development and risk-aware LLM use.

Design and build AI-powered internal systems for support, legal, finance, and other functions; own production infrastructure, observability, and operational practices; embed with cross-functional partners to prioritize and deliver tooling; extend company AI infrastructure to internal use cases and establish engineering patterns for scaling.

Lead design and implementation of enterprise systems and AI solutions, sustain global application infrastructure, enforce SDLC/change management, run NOC monitoring and incident resolution, engage clients to gather requirements, maintain documentation and policies, and support budgetary planning for applications development teams.

Develop, optimize, and ship video processing, generative video, and 3D reconstruction algorithms (e.g., NeRF, 3D Gaussian Splatting) across desktop and mobile. Integrate and deploy deep learning models, run research and evaluations, build production-ready modules, and create test environments and tools for runtime verification of video and 3D pipelines.