Top Artificial Intelligence Jobs

The AI Engineer will design and build production systems, focusing on LLM integration, system reliability, evaluation frameworks, and high-quality product features while maintaining strong engineering practices.

As a Senior Agentic AI Engineer, you'll develop core systems for AI agents, focusing on reliability, observability, and production readiness, working hands-on with distributed systems and orchestration.

The Enterprise AI Lead will manage relationships with clients, develop commercial strategies, drive initiatives across teams, and present to executives, requiring strong communication and problem-solving skills.

Lead design, development, and deployment of enterprise-scale Generative and Agentic AI solutions. Architect production-ready multi-agent systems, LLM-powered chatbots, and scalable AI platforms. Define standards, governance, guardrails, and best practices; integrate AI with enterprise systems and implement prompt engineering and RAG strategies to improve conversational and automation workflows.

Lead the strategy and development of digital and AI solutions for university partners to enhance the online program lifecycle, improve efficiencies, and drive measurable outcomes.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

The Founding AI Engineer will build production AI systems for nuclear deployment, focusing on fine-tuning, R&D, and collaborating with top tech partners. Responsibilities include designing eval infrastructure, owning fine-tuning pipelines, and pushing the frontier of AI applications relevant to nuclear operations, ensuring high-quality outputs and continuous improvement.

This role focuses on sourcing, due diligence, and portfolio support in the AI investment ecosystem. It requires strong networking and analytical skills, combined with a proactive entrepreneurial spirit.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

As a Software Engineer, you'll develop AI scheduling agents to coordinate meetings across various complexities, improve architectures, and analyze agent performance.

The AI Platform Engineer manages Oracle Cloud Infrastructure and supports AI agent deployment, DevOps, automation, and security for ERP Suites.

The AI Scientist will lead the development of biomolecular modeling technologies, focusing on creating and validating AI models for drug design using experimental feedback.

The AI Platform Engineer will develop full-stack systems connecting AI models to real-world applications in drug design, collaborating with scientists and ensuring rapid experimentation cycles.

The Applied AI/Bio Scientist will utilize AI to design biologics, collaborate with teams, and improve discovery processes in therapeutic design.

The AI Engineer will develop AI-powered revenue platforms, work on AI infrastructure, approval workflows, and intelligent collections agents, focusing on reliability and customer needs.

The AI Strategist will serve as a client-facing SEO/GEO expert, translating AI insights into actionable recommendations, while building and defining Evertune's strategic client playbook for AI visibility and performance improvement.

Lead strategy and architecture for GTM and finance systems (Salesforce, NetSuite, Data360/Snowflake, Agentforce). Manage a Salesforce admin, design and operate autonomous Agentforce agents, ensure data governance and a unified customer profile, oversee API integrations and migrations, and build testing and release processes to maintain system integrity and compliance.

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

The role involves developing, training, and deploying machine learning models, building data pipelines, and collaborating with teams for integration and performance optimization. It supports the ML lifecycle from data collection to monitoring.

Design, develop, and deploy scalable software systems focusing on Python, collaborate with teams to solve complex problems, and optimize system performance.

Lead enterprise AI enablement strategy and team to scale governed, responsible AI (e.g., Microsoft 365 Copilot) across the U.S. and Europe. Drive role-based training, prompt libraries, champions network, change management, governance integration, adoption metrics, vendor/licensing relationships, and replace shadow AI with sanctioned tools.

The Full Stack AI Engineer will build and deploy AI-integrated MVPs, develop front-end and back-end systems, optimize ML pipelines, and maintain APIs and cloud infrastructure, focusing on healthcare administration.

The role involves shaping technology development governance, managing stakeholder ecosystems, executing transactions, and maintaining relationships across the tech landscape.

The intern will work on AI algorithms for spacecraft design, collaborating on generative design and systems engineering. Responsibilities include building models, conducting simulations, and integrating AI outputs into workflows.

As a Full Stack AI Engineer, you'll build AI applications and products, prototype solutions, and collaborate with founders in a fast-paced environment.