Top Artificial Intelligence Jobs

Drive product strategy and execution for Cloud Provider and AI Networking segments. Collaborate with teams to define product requirements, assess market opportunities, and develop go-to-market strategies for Tier 1 and Tier 2 customers.

Define and build internal AI tooling strategy: prototype, deploy, and maintain LLM-powered systems and agents for information retrieval, document analysis, workflow automation, and developer assistance. Drive end-to-end lifecycle, evaluation, observability, and best practices across the company as the first AI-focused engineer on the Internal Software Tools team.

Design and build agent infrastructure and orchestration for AI-driven products; implement observability, tracing, evals, guardrails, and tooling to deploy, monitor, and improve LLM-based systems in production.

Assist in deploying and monitoring Cerebras AI infrastructure, perform troubleshooting, collect telemetry, and learn through shadowing senior engineers.

The Senior Manager, AI Performance & Operations is responsible for the performance and improvement of AI workflows, incident response, designing evaluation systems, and stakeholder communication.

Design, develop, and deploy AI-driven healthcare solutions, conduct evaluations, mentor junior engineers, and ensure compliance with healthcare standards.

Develop and optimize a deep learning compiler stack (using LLVM/MLIR) that lowers neural networks from frameworks (PyTorch/TensorFlow/Caffe) to efficient code for embedded/special-purpose platforms, implement NN operation kernels, create optimization and scheduling strategies for multicore/DSP/accelerators, benchmark performance, and collaborate with hardware designers and partners.

The role involves enhancing AI system reliability, developing service objectives, monitoring infrastructure, leading incident responses, and collaborating across teams.

The Solutions Architect will serve as a technical advisor, guiding customers through the integration and deployment of AI technology, with a focus on developing scalable architectures and ensuring successful adoption of Claude systems.

As a Solutions Architect, you will advise government agencies on integrating LLM solutions, guiding them through the adoption process and ensuring technical alignment with business goals.

Lead the development and management of AI infrastructure, ensuring optimal performance of systems and providing mentorship to engineers while deploying advanced AI models.

Develop a deep-learning compiler stack that converts neural network descriptions into optimized code for embedded and special-purpose platforms. Implement and optimize NN operations, use LLVM/MLIR, benchmark on DSPs/accelerators, devise multiprocessor partitioning/scheduling, validate runtimes, and collaborate with hardware designers and partners.

Lead a team of Growth Account Executives to drive revenue growth and retention with startup customers, establish processes, and mentor team members.

Serve as the global go-to-market owner for Tenable AI Exposure: define positioning and messaging, influence product roadmap with customer insights, lead product launches, create sales and marketing assets, enable demand generation and sales, engage practitioner and enterprise communities, and collaborate cross-functionally to drive adoption and growth.

Support AI capability and adoption through prompt engineering, structured experimentation, testing custom GPTs, documenting prompt libraries and exemplars, coaching users, prototyping lightweight AI workflows, and contributing enablement materials.

Lead day-to-day AI capability and enablement: translate AI strategy into coaching, triage, experimentation, and scalable guidance. Provide hands-on AI coaching and experimentation, manage intake and routing workflows, capture recurring patterns into reusable artifacts, coordinate cross-functional stakeholders, run enablement initiatives, and track adoption and performance metrics to improve AI usage across the firm.

Collaborate to enhance product through analytics, conduct data exploration on user behavior, and present insights to influence product decisions.

The Azure Cloud Engineer will design, implement, and maintain Azure solutions, govern AI platforms, and manage infrastructure automation and deployment workflows. Responsibilities include over-seeing cloud architecture, building CI/CD pipelines, and ensuring compliance with security standards while mentoring teammates in cloud infrastructure best practices.

Provide legal support for privacy and AI governance: draft and negotiate privacy/AI-related contracts, lead Privacy by Design and impact assessments, develop governance policies and playbooks, manage cookie compliance, RoPAs, and DSARs, advise product and engineering on risk mitigation, respond to customer privacy/AI inquiries, monitor global privacy and AI regulations, and engage with regulators and works councils as needed.

Lead system-level architecture and detailed design of ultra-low-power analog and digital AI accelerators. Translate product requirements into block-level specs, explore novel intelligence representations, develop system models with Synopsys Platform Architect, inform RTL and verification, and collaborate across compute IP, firmware, physical design, and partners while providing technical leadership and mentorship.

Design, develop, and productionize scalable AI tools for systems engineering in autonomous vehicles, integrating data for traceability, and building backend services.

The Level 3 Support Analyst - AI Specialist resolves complex technical issues for customers, focusing on AI solutions, troubleshooting, and collaborating with multiple teams. Responsibilities include investigating issues, mentoring junior staff, and providing 24/7 emergency support.

Design and deploy AI capabilities for U.S. federal agencies, focusing on integrating AI models with government systems, and ensuring ethical standards.

The role involves building deployment tools for classified environments, maintaining documentation, and developing CI/CD pipelines, requiring extensive experience in programming and cloud technologies.

As a Senior/Lead Backend Engineer, you'll design scalable backend systems and data pipelines for AI capabilities, ensuring data quality and system reliability while mentoring peers.