Top Artificial Intelligence Jobs

The Senior Machine Learning Engineer will develop and maintain algorithms/services for multi-agent AI, deliver cloud-native architecture, and optimize ML models for performance.

The AI Platform Engineer is responsible for building and securing AI infrastructure, managing Kubernetes environments, implementing CI/CD pipelines, ensuring compliance, and collaborating with teams to enhance platform performance and reliability.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

Design and launch intelligent security products using AI tools; own product lifecycle from conception to deployment, collaborating cross-functionally. Rapid prototyping and leveraging data to identify opportunities and validate directions are core responsibilities.

Act as primary business and technical post-sale partner to onboard, operationalize, and scale the platform across security workflows. Lead onboarding, drive adoption, manage customer health and escalations, align stakeholders, and surface product feedback to influence roadmap and ensure measurable outcomes and expansion.

Design and implement AI-driven solutions, collaborate with stakeholders, and scale AI knowledge across the organization. Foster AI adoption and develop scalable frameworks.

The AI Engineer will design and implement AI systems, develop solutions for production environments, and partner with teams to improve operations through AI integration.

The AI Engineer will launch GenAI solutions, build AI systems, and collaborate with teams to enhance production environments and address challenges.

The AI Product Manager oversees the strategy, roadmap, and execution of AI solutions, collaborating with teams to address operational challenges and ensure product safety and effectiveness while monitoring performance.

The GCP GenAI Engineer will design and implement Generative AI solutions on Google Cloud, focusing on deployment, security, and connectivity, while supporting CI/CD pipelines and infrastructure as code.

The AI Product Manager will define the strategy and execution for Generative AI solutions, manage the product lifecycle, drive integration strategies, and ensure AI safety and performance in collaboration with engineering and application teams.

Lead development of a production autonomous-agent intelligence layer: implement closed-loop learning from trade outcomes, build evaluation and automated strategy generation, monitor fleet performance, manage risk and capital allocation, own model training/inference pipelines (including LLM hosting/fine-tuning), and build telemetry and data capture for real-time market adaptation.

The role involves leading engineering initiatives in cybersecurity AI, developing architectures, collaborating cross-functionally, and integrating AI capabilities into solutions, ensuring operational readiness and standards compliance.

The Director of AI Programs leads AI initiatives in a healthcare organization, focusing on strategy, implementation, compliance, and operational performance. This role collaborates with executives and healthcare stakeholders to optimize AI tools for clinical efficiency and innovative patient care.

As a Lead Engineer in Cyber AI, you will lead engineering initiatives in cybersecurity, develop AI solutions, and collaborate with teams to enhance capabilities.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

As a Principal AI Engineer, you'll design scalable AI systems, mentor teams, develop large-scale LLMs, and optimize AI-driven cybersecurity solutions.

As a Staff AI Solutions Architect, you will design, implement, and deploy AI solutions for cybersecurity, ensuring performance and security in production environments while mentoring engineers and collaborating across teams.

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

The CX Manager will own the ERP integration domain, providing problem-solving expertise for complex customer issues and ensuring efficient issue resolution related to ERP systems and AI operations.

The Solutions Architect will engage with strategic customers, design end-to-end solutions for AI-driven engineering workflows, and provide guidance on adoption strategies while collaborating with account teams and product stakeholders.

As a Staff Software Engineer, you will design, develop, and enhance AI and machine learning applications and services, collaborating closely with cross-functional teams to ensure high-quality standards.

The Application Engineer will develop AI Physics capabilities, work with customers to tailor solutions, and enhance product features based on customer feedback. Responsibilities include building AI-ready data pipelines and debugging complex issues in workflows.

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.

Design and maintain scalable data pipelines and ETL/ELT workflows; build and operate training, deployment, and model-serving infrastructure; develop feature stores and vector databases; ensure reliability, low latency, and observability; collaborate with Research/Data Science to productionize models; contribute to infrastructure-as-code and cloud documentation.