Top Artificial Intelligence Jobs

Leads integration engineering, platform modernization, AI-enabled automation, testing, and quality assurance across pharmacy and consumer wellness technology organizations. Oversees cloud-native and legacy platforms, AIOps, AI/ML and LLM adoption, CI/CD, incident management, roadmaps, budgets, vendor relationships, and engineering teams. Establishes quality standards, metrics, OKRs, and operational practices while driving technical debt reduction, cost optimization, workforce development, and reliable delivery.

Leads Faraday Future’s business, user ecosystem, sales, partnerships, and regional operations across the U.S. Northeast. Owns regional P&L, revenue growth, strategic accounts, partner relationships, New York office operations, cross-functional coordination, market intelligence, and team development. Requires extensive business development, sales, or general management experience, strong Northeast market knowledge, and leadership in robotics, AI, automotive, or high-tech industries.

Leads AI strategy and transformation consulting engagements, including readiness assessments, use-case prioritization, roadmaps, operating models, business cases, responsible AI governance, adoption programs, and value realization. Advises senior executives, coordinates business and technical teams, develops consulting offerings, drives business development, and mentors consultants. The role requires strong AI and data fluency, transformation leadership, executive facilitation, stakeholder management, and experience delivering measurable client outcomes.

Leads AI strategy and transformation consulting engagements, advising executives on AI readiness, use-case prioritization, operating models, business cases, governance, adoption, and value realization. Develops roadmaps, facilitates workshops, coordinates business and technical teams, supports process redesign, mentors consultants, and drives proposals, offerings, and client business development.

Owns the enterprise strategy, roadmap, governance, service delivery, and adoption of Microsoft Copilot Studio and agent capabilities. Evaluates AI features, licensing, costs, security, compliance, and operational readiness; establishes governance and operating models; develops enablement, training, documentation, monitoring, and administration processes; and leads cross-functional initiatives supporting scalable enterprise AI adoption.

Builds, evaluates, secures, and supports production AI-native software. Responsibilities include developing agentic AI solutions, using coding assistants across the SDLC, evaluating models, gathering requirements, reviewing designs and code, managing changes and vendors, supporting production systems, and leading large projects. The role requires strong software engineering fundamentals and experience with AI agents, LLM/SLM applications, cloud-native development, secure APIs, and Amazon Bedrock AgentCore.

Owns customer forecasting, demand planning, backlog placement, and revenue execution for major Cloud and AI semiconductor customers. Analyzes infrastructure investments, market trends, capital expenditures, rack-level silicon content, and competitive dynamics to improve forecast accuracy and supply alignment. Coordinates Sales, Finance, Supply Chain, and Business Units, influences strategic decisions, identifies revenue-growth opportunities, and drives execution of customer commitments, supply plans, and risk mitigation.

Lead and develop a team of Data Partnerships Associates responsible for sourcing, pitching, onboarding, and closing enterprise data partnerships. Set priorities, manage pipelines, handle complex partner escalations, translate AI lab requirements into sourcing strategies, and collaborate with Legal, Finance, and Operations. Build scalable processes and playbooks while ensuring partnerships meet data quality, privacy, and compliance standards.

Build and maintain production AI agents, data pipelines, backend services, and supporting infrastructure. Develop tools to run, evaluate, and monitor AI agents; deploy large language model applications; and collaborate with product and security teams on AI-driven features. The role also involves tracking advances in language models and agent techniques and applying improvements to the product.

Leads strategy, roadmaps, business cases, adoption, and value measurement for enterprise AI products, beginning with AI-driven field-service dispatch optimization. Partners with data science, engineering, operations, finance, marketing, IT, and vendors to deliver measurable business outcomes, manage pilots and rollouts, establish responsible AI practices, and build a scalable AI product function.

Design, build, deploy, and maintain scalable cloud-native data platforms, pipelines, lakes, warehouses, and analytics solutions. Support data science, AI/ML, and business intelligence initiatives while processing structured and unstructured data. Lead collaborative teams, guide analysts and developers, assess cloud architectures, and support migration and modernization efforts for mission-driven clients.

Develop and deploy machine learning models and data solutions using Python, R, and SQL. Clean, analyze, and visualize structured and unstructured data; apply statistical and supervised or unsupervised learning methods; build dashboards and lightweight applications; integrate systems; and advise clients on data-driven decisions. Lead algorithm and system development while collaborating with clients and teammates. A TS/SCI clearance with polygraph and bachelor’s degree are required.

Design and build integrations connecting legacy practice management systems to an AI platform. Responsibilities include AI-assisted schema mapping, data modeling, ETL pipelines, REST/SOAP APIs, data cleansing, quality monitoring, production troubleshooting, documentation, and collaboration across architecture, product, engineering, and operations teams. The role requires applying LLM tools to schema inference, field reconciliation, anomaly detection, and data-quality automation while handling healthcare data securely.

Lead AI partnership strategy, source and evaluate strategic technology partnerships, build business cases, conduct due diligence, negotiate complex deals, and manage partner relationships. The role coordinates execution across product, engineering, legal, marketing, and senior leadership while monitoring the AI industry landscape to identify growth and engagement opportunities for Pinterest.

Tenure-track faculty member conducting research and teaching at the intersection of human cognition and artificial intelligence. Responsibilities include scholarship, undergraduate teaching, curriculum and program development, advising, mentoring undergraduate research, and collaboration across Barnard and Columbia. The role requires a PhD in Computer Science, Cognitive Science, or a related discipline, along with a strong research agenda and commitment to inclusive undergraduate education.

Leads an eight-person engineering team building AI agents, conversational analytics, data intelligence, voice agents, and their shared context graph and data platform. Owns technical strategy, architecture, delivery, hiring, reliability, security, tenant isolation, evaluation systems, and agent safety. The role remains hands-on, involving prototyping, coding, debugging, architecture reviews, production monitoring, and continuous improvement. Partners with product, design, customers, and forward-deployed engineering to turn freight-industry needs into scalable AI platform capabilities.

Lead strategy and roadmap for Virta’s end-to-end consumer member experience. Identify high-impact opportunities, develop personalized and adaptive experiences using data and AI, establish experimentation frameworks, and align Product, Design, Engineering, Clinical, Coaching, Operations, and executive stakeholders. The role translates complex healthcare and care-delivery needs into intuitive products, guides company-level investment decisions, evolves the care model, and mentors product leaders.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering judgment, reasoning quality, usefulness, correctness, and user guidance. Provide clear written feedback, distinguish response-quality levels, help define evaluation standards, and record brief video explanations. This flexible remote contract requires strong software engineering experience, familiarity with AI-assisted development workflows, and excellent English communication.

Builds and enables responsible AI solutions across the organization. Responsibilities include managing AI use-case intake, coaching teams, developing Copilot Studio agents and Power Platform automations, supporting AI-powered developer tools, establishing governance and repeatable patterns, measuring adoption, and delivering training. The role requires strong communication, software development or architecture experience, Microsoft Copilot Studio expertise, and Microsoft 365 administration experience.

Manage AIUC’s San Francisco office, including facilities, vendors, supplies, workplace technology, onboarding and offboarding, access management, payroll coordination, compliance administration, and office systems. Build SOPs, inventories, calendars, and checklists to make operations scalable and reliable. The role requires hands-on IT and hardware support, strong organization, vendor management, and in-person work five days per week.

Modernize enterprise IT operations through cloud engineering, platform engineering, infrastructure-as-code, automation, and AI-assisted workflows. The role designs AWS and Azure infrastructure, self-service capabilities, event-driven remediation, identity and endpoint automation, CI/CD pipelines, and safe agentic operating patterns. It also establishes engineering standards, observability, auditability, rollback controls, and metrics while troubleshooting complex cloud, networking, identity, API, and distributed-systems issues.

Lead the architecture and development of Cisco’s enterprise AI defense platforms, including control planes, data planes, policy engines, and security services. Build high-throughput Go and Python microservices, secure agentic AI and MCP workflows, and implement protections against prompt injection, jailbreaks, tool abuse, and data exfiltration. Drive zero-trust architecture, cross-functional technical strategy, production delivery, engineering standards, and mentorship across security research, product, and platform teams.

Support the design, development, testing, and deployment of AI-powered applications across front-end, back-end, and data workflows. Collaborate with engineers, researchers, product managers, and operators to translate customer needs into product requirements, integrate AI models, evaluate outputs, improve reliability and usability, and ship production-grade tools for government, healthcare, and industrial customers.

AI/ML engineering intern will help design, build, evaluate, and deploy LLM-powered applications and machine learning systems. Responsibilities include developing data pipelines, working with structured and unstructured data, supporting model training and optimization, preparing systems for production monitoring, and collaborating with engineers, researchers, and product teams. The role offers mentorship and hands-on experience applying AI to healthcare, government, and energy workflows.

Interns build backend services, APIs, distributed systems, platform components, developer tools, and AI/ML infrastructure. Responsibilities span design, implementation, testing, deployment, maintenance, reliability, performance optimization, observability, and collaboration with Product, ML, Infrastructure, and customer-facing teams. The role is intended for undergraduate juniors and seniors graduating by June 2028 and offers mentorship through production-focused engineering work.