Top Artificial Intelligence Jobs

Partner with customers to design, prototype, and deploy AI-enabled cybersecurity workflows using OpenAI models and tooling. Provide technical leadership across AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, cloud security, identity, and GRC automation. Build demos, pilots, and reference architectures; define success criteria, data needs, integrations, and safety guardrails; and translate executive outcomes into practitioner-level implementations while producing reusable field assets and product feedback.

Lead design, build, and operation of production AI systems and inference stacks (vLLM) across AI Factory platforms. Implement RAG, MLOps, storage/networking, Kubernetes/containers, monitoring, security, and on-call incident response. Mentor engineers, engage clients, author runbooks, and contribute reusable patterns and tooling.

Design and build AI-enabled helpdesks and contact centers: implement agentic AI that plans and interacts, develop configurable front- and back-end systems, and solve customer problems with modern full-stack tools.

As a Senior Embodied AI Engineer, you will design and deploy intelligent control systems, manage simulations, and apply machine learning methodologies to enhance robotic performance in manufacturing environments.

Lead strategic ISV partnerships and manage Dialpad's App Marketplace to drive integrations, adoption, co-sell/resell revenue, and marketplace monetization. Negotiate agreements, build joint business plans, track partner performance, and coordinate cross-functional teams to implement API integrations and go-to-market initiatives.

The Finance Transformation AI Manager leads the design and deployment of AI solutions for finance, manages teams, budgets, and client relationships, ensuring quality and alignment with business objectives.

The Enterprise AI Lead will manage enterprise customer relationships, drive commercial strategy, and lead cross-functional initiatives in AI-driven solutions.

As a Software Engineer, Applied AI, you'll architect and implement integrations and scalable solutions for enterprise clients, focusing on technical requirements and business goals.

The Applied AI Engineer will architect, implement, and maintain AI agents for Edison's platform, collaborating with science and engineering teams and gathering insights from R&D partners to improve the agents' capabilities and reliability.

The AI Search Manager will onboard and advise clients on utilizing Peec AI products for visibility in AI-driven search, encompassing sales, strategy, and performance reviews.

The role involves building and deploying AI-native data solutions, focusing on LLM and agent development, automation workflows, and data analysis, while leveraging cloud technologies.

The Applied AI Scientist will develop AI features, improve orchestration and reasoning systems, and work closely with engineering teams on production capabilities.

Build and operate production-grade infrastructure for real-time LLM workloads and Conversational Intelligence: reliable event-driven messaging, state/session management, observability, service boundaries, and production support including on-call and incident response. Mentor peers and harden platform interfaces for scalability and reliability.

Lead end-to-end strategic alliances with Snowflake and Databricks, owning joint business plans, go-to-market strategies, co-sell motions, integrations, and co-marketing. Drive partner-sourced pipeline and influenced revenue while coordinating cross-functional enablement and tracking partnership KPIs.

Own and grow strategic partnerships with foundation-model providers (OpenAI, Anthropic). Build joint go-to-market motions, drive partner-sourced/influenced pipeline, define joint solutions and reference architectures, coordinate cross-functional teams, manage partnership KPIs, and represent partners internally while maintaining deep technical and roadmap knowledge.

Lead product strategy and execution for foundational platform capabilities powering C3 AI products. Run discovery with customers and internal teams, define API/SDK requirements, prioritize investments using metrics, partner with engineering/architecture on trade-offs, drive releases and adoption, and ensure platform support for commercial and regulated deployment models.

Senior AI Engineer to design, develop, and productionize machine learning and AI systems for proprietary trading. Collaborate with researchers and traders to implement, optimize, deploy, and monitor models and scalable infrastructure, and contribute to technical direction and mentoring.

Implement AI powered workflows and applications, design novel AI architectures, and build evaluation pipelines for internal and customer-facing products.

As a Forward Deployed AI Engineer, you will integrate Latent Labs' AI models with pharmaceutical clients' workflows, focusing on tech deployment, customer advocacy, and collaborative feedback for product improvement.

Own AI solution vision and delivery from intake through production. Define product and business requirements, manage backlogs and sprints, run stakeholder communications and demos, set acceptance criteria and KPIs, coordinate handoffs to platforms, ensure responsible AI practices, and manage multiple concurrent prototyping-to-production engagements.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

The AI Engineering Intern will develop and enhance Large Language Models to improve task workflows, automate processes, and prototype AI features for client productivity.

Lead enterprise AI strategy and roadmap, build and mentor cross-functional AI/ML teams, drive frontier research and rapid prototyping, translate models into production, align initiatives with business priorities, and represent the company externally.

As a Senior AI/ML Platform Engineer, you will architect and scale the ML platform, ensuring efficient ML workflows and collaborating with various teams to drive AI adoption.