Top Artificial Intelligence Jobs

Leads new business development, account growth, commercial discussions, client relationships, and sales operations for AI and GenAI data solutions. Partners with engineering, delivery, and customer success teams to understand frontier lab needs, structure projects, close opportunities, and expand client accounts. Requires quota-based technology sales experience, startup experience, STEM education, and strong AI/ML market knowledge.

AI Engineer Interns will research, design, evaluate, and productionize AI-powered data capabilities. Responsibilities include running AI/ML experiments, developing agent self-improvement and continuous-learning systems, collaborating with product engineers, building evaluation and training infrastructure, optimizing performance, designing APIs, and contributing across the full development lifecycle.

Leads communications strategy across the Americas for S&P Global Energy. Develops public narratives, press releases, media advisories, and internal content; builds relationships with journalists, analysts, influencers, senior leaders, and subject matter experts; coordinates interviews, briefings, and events; monitors communications performance; and manages crisis communications and rapid-response efforts.

Develop end-to-end data and machine learning capabilities for Special Operations users. Responsibilities include building scalable pipelines, transforming large datasets, applying advanced analytics and machine learning, deploying models and inference services, developing APIs, and delivering analyst-facing applications. The role requires collaboration with mission users, analysts, engineers, and technical leadership in a customer-site environment.

Build and operate Arm’s production AI platform infrastructure, including model gateways, MCP services, and control-plane components. Own scalability, reliability, observability, security, incident response, automation, lifecycle management, and operational readiness. Develop infrastructure-as-code and GitOps workflows, secure runtime patterns, telemetry, monitoring, alerting, and support processes across Kubernetes, cloud, identity, networking, secrets, and compliance systems. Participate in a paid on-call rotation for high-impact incidents.

Provides end-to-end application and infrastructure support for production systems, ensuring stability, availability, and performance. Responsibilities include monitoring environments, troubleshooting incidents, supporting ITIL incident/problem/change management, analyzing operational trends, and escalating issues. The role also promotes validated AI-assisted engineering practices, automation, secure coding, testing, and remediation. Required technical experience includes Python, Terraform, Kubernetes, microservices, public cloud, observability tools, and large-scale technology environments.

Leads New York Life’s AI Center of Excellence across frontier AI provider relationships, AI software lifecycle standards, platform architecture, governance integration, talent acquisition, upskilling, and production delivery. Builds and manages West Coast AI engineering teams, evaluates emerging AI technologies, establishes scalable governance and engineering practices, and owns measurable business outcomes from enterprise AI solutions. Provides senior leadership coverage for West Coast partners and coordinates with Home Office leadership.

Own the product strategy, roadmap, and execution for DigitalOcean’s managed agentic AI infrastructure products. Define developer experiences, APIs, CLIs, documentation, pricing, packaging, and launch plans for services supporting long-running agents, tool execution, state management, secure sandboxes, identity, observability, and scale. Partner with customers, engineering, finance, security, legal, design, and go-to-market teams to turn emerging agent infrastructure needs into reliable, commercially successful products.

Design, build, deploy, and operate production-grade AI agents, automations, and internal tools. Lead workflow discovery, multi-agent orchestration, context and state management, integrations, full-stack interfaces, evaluation, guardrails, testing, monitoring, and staged releases. Measure business outcomes and determine when agents, simpler automation, or no solution is appropriate. The role requires ownership of agent systems from architecture through production improvement and reuse.

Develop and maintain scalable backend applications and services using Java, J2EE, Spring Boot, APIs, microservices, and distributed systems. Integrate AI, machine learning, generative AI, AI agents, and MCP capabilities into enterprise applications. Design software architectures, implement testing and CI/CD, optimize performance, support cloud-native deployments, and ensure security, reliability, observability, and operational readiness.

Lead and develop a North American BDR team, overseeing inbound and outbound pipeline generation, lead qualification, forecasting, coaching, and talent development. Design scalable outbound campaigns, improve routing and handoff processes, analyze performance signals, and partner with Sales, Marketing, Operations, Enablement, and Channel teams. Use sales technology and AI-enabled workflows to improve productivity and decision-making. This hybrid Austin-based role includes occasional travel and monthly leadership travel on average.

Leads full-stack software engineering for JPMorganChase’s Wholesale Credit Risk technology team. Designs, develops, tests, troubleshoots, and reviews secure production code; improves application resilience and operational stability; promotes responsible AI-assisted engineering practices; automates recurring remediation; and evaluates architectures and technologies with vendors and internal teams. The role requires cloud-native development, agile SDLC expertise, financial services knowledge, data architecture, modern front-end technologies, GraphQL, and API development.

Own the research agenda for AI model training and evaluation, including developing new training objectives and evaluation metrics. Connect research outcomes directly to revenue and product performance in a fast-moving social AI startup. The role requires high ownership, comfort with ambiguity, strong motivation, software engineering experience, and in-person work at the Palo Alto office.

Own the system that enables AI characters to remember users across hundreds of conversations, including memory schema design, information extraction, and compression. Develop and evaluate improvements based on user retention and recall accuracy. Work with a small, fast-moving engineering team in person at the Palo Alto office, taking ownership of ambiguous problems and defining effective solutions.

Lead design and deployment of physics-based, ML, and LLM-powered modeling and agentic AI systems for semiconductor process, packaging, and manufacturing workflows; architect integrations with design automation and fab/test platforms; benchmark and improve models; and translate results into actionable insights and visualizations.

Own the full lifecycle of AI products, from discovery and roadmap definition through prototyping, deployment, adoption, and measurable business outcomes. Build GenAI and agentic AI solutions using LLM APIs, tool calling, structured outputs, and evaluation. Partner with data engineering on pipelines, data quality, governance, security, and observability. Lead agile backlog management, UX collaboration, training, change management, and continuous improvement while translating ambiguous business needs into production AI applications.

Lead the vision, strategy, roadmap, portfolio, and go-to-market execution for AI inference cloud services. Partner with engineering, customers, sales, marketing, and industry partners to solve scaling and optimization challenges across specialized GPU infrastructure. Evaluate AI and cloud technology trends, define differentiated inference capabilities, translate customer needs into product investments, and drive business growth through innovative AI cloud products.

Lead go-to-market strategy and strategic sales for AI and Neocloud accounts. Build executive relationships with hyperscale cloud and data-center customers, manage complex negotiations and long-term agreements, develop ecosystem partnerships, maintain forecasts and pipeline visibility, and collaborate cross-functionally to deliver infrastructure solutions at scale.

The Senior Accountant oversees monthly, quarterly, and annual close processes; prepares financial statements, audit schedules, and reports; researches accounting policies; maintains internal controls; identifies financial-system issues; and drives process improvements. The role may review teammates’ work, support treasury projects, train colleagues, and provide performance feedback while communicating with management and coordinating department initiatives.

Lead the architecture and development of agentic, conversational, and information-retrieval experiences for a consumer voice product. Design and ship ML-based user experiences, build model development and evaluation infrastructure, optimize inference for latency and reliability, and guide a focused multidisciplinary team. The role partners closely with founders and backend, iOS, ML, infrastructure, and design engineers.

Own the full sales cycle for warm inbound SMB opportunities, responding quickly, qualifying prospects, delivering product demos, managing CRM records, handling objections, negotiating, and closing deals within 30 days. The role requires meeting activity and revenue targets, collaborating with sales leadership, participating in coaching, and articulating the value of AI-driven insurance compliance solutions. This is a fully remote position with minimal conference travel.

Tenure-track Assistant Professor of Computer Science responsible for teaching undergraduate courses across the curriculum, conducting research with undergraduate students, developing innovative instruction, and contributing to multidisciplinary collaborations and student Applied Groups. The role requires participation in Earlham’s liberal arts mission, inclusive community, and principles and practices.

Conduct investment manager due diligence, asset class research, portfolio construction, asset allocation, asset/liability modeling, and macroeconomic research. Produce investment analysis and reports for institutional clients, support client-facing presentations and project management, assist with RFP responses, and help drive scalable AI adoption in investment research.

Leads Haymarket’s healthcare media sales organization, developing revenue strategies, exceeding targets, building high-performing teams, and securing complex partnerships with pharmaceutical, medical device, and healthcare clients. The role manages senior client relationships, forecasts revenue, analyzes sales performance, and applies digital marketing, data-driven, omnichannel, and AI strategies to drive growth.

Designs and deploys advanced machine learning and deep learning models, leads improvements to AI/ML systems, oversees algorithm development through integration and sustainment, analyzes complex datasets, and communicates technical insights to stakeholders. The role requires extensive experience with algorithms, MLOps pipelines, statistical analysis, experimental design, data storytelling, data governance, and data quality, plus an active Top Secret clearance and eligibility for SCI.