Top Artificial Intelligence Jobs

As a Product Architect, you will analyze DRAM system architectures, identify bottlenecks, lead innovations, define memory features, and mentor junior engineers.

Develops and scales generative AI and automation solutions for memory circuit design, layout, verification, simulation, and tapeout workflows. Uses engineering and silicon data for predictive insights and optimization of floorplanning, placement, routing, and validation. Collaborates with design, CAD, product, manufacturing, and process teams to reduce manual effort, improve quality, and accelerate time-to-tapeout. Requires production-quality Python development and experience applying machine learning, data analysis, or automation to engineering workflows.

Design, build, and scale reliable agentic AI systems and infrastructure (orchestration, sandboxed execution, latency optimization, memory, multimodal I/O). Productionize frontier AI algorithms, collaborate with ML/security/product teams, mentor engineers, and deliver production-grade, performant code that advances enterprise AI assistant capabilities.

Leads the Salesforce ecosystem, web applications, and Oracle ERP integrations across global sales, service, and manufacturing operations. Owns business systems strategy, roadmap, governance, support service levels, projects, vendors, security, compliance, data quality, automation, and AI adoption. Partners with business stakeholders, oversees system development and deployment, manages application support escalations, and leads business systems analysts, administrators, developers, and external service providers.

Build and productionize reliable, scalable agentic AI systems (orchestration, sandboxed execution, latency optimization, agent memory, self-reflection, knowledge graphs, multimodal I/O). Implement frontier AI algorithms, ship production-grade code, mentor engineers, collaborate with ML, security, product, and UX teams, and drive roadmap and reliability improvements.

Design, develop, and deploy scalable Voice AI platforms and distributed systems across regions and datacenters. Build audio acquisition, conversation management, speech generation, model integrations, and voice harness capabilities. Partner with product managers and customers, improve SRE tooling, enforce software engineering best practices, and mentor engineering colleagues. The role requires extensive experience with LLM applications, AI agents, programming, Kubernetes, and highly available workloads.

Leads the AI strategy and architecture for supply-chain planning operations. Builds production machine-learning, data-stitching, anomaly-detection, scenario-modeling, alerting, and agentic workflow capabilities across enterprise planning systems. Establishes MLOps, governance, observability, security, and explainability practices while partnering with planners, engineering, manufacturing, procurement, finance, and executives to deliver trusted operational decision support.

Leads portfolio planning and cross-functional execution for Data Science Core and GenAI Studio programs. Establishes roadmaps, operating rhythms, priorities, dependencies, risk management, readiness criteria, decision processes, and success measures. Coordinates data science, engineering, product, research, privacy, legal, security, and business stakeholders from problem framing through deployment, adoption, and monitoring. Communicates technical tradeoffs and responsible AI considerations while improving team effectiveness, capacity planning, documentation, and delivery practices.

Summer 2027 PhD research internship at Atlassian focused on AI research. The role supports distributed-first collaboration, with virtual interviews and flexibility to work remotely or from a company office.

Conduct AI research as a 2027 graduate hire at Atlassian, collaborating remotely or from company offices. The provided description contains no specific research area, responsibilities, qualifications, or technical requirements.

Lead and grow Cloudflare’s models team responsible for model integrations, launches, catalog accuracy, pricing, reliability, evaluations, rankings, auto-routing, and provider coordination. Build automation and agent workflows, monitor model health, detect regressions, and turn Gateway traffic data into trusted recommendations. The role combines people management, technical execution, product judgment, operational scalability, and hands-on debugging across AI model providers.

Build and deploy secure, production-grade AI solutions for go-to-market teams using retrieval, structured-data querying, and agentic workflows. Partner with GTM leaders to define AI strategy, roadmaps, and build-versus-buy decisions. Establish monitoring, evaluation, security, and ROI frameworks tied to revenue outcomes. Drive adoption through enablement and feedback loops, develop reusable AI architecture and data connectors, improve engineering standards, and mentor other engineers.

Build and operate Affirm’s AI platform, including LLM and MCP gateways, agent runtimes, evaluation services, and governance controls. Design highly available backend systems, manage identity, quotas, routing, caching, reliability, observability, and security for AI workloads. Own projects from design through launch and on-call, establish engineering standards, collaborate across teams, mentor engineers, and help scale AI systems into production.

Build and manage a self-sourced sales pipeline, run discovery and product demonstrations, design customer pilots, negotiate pricing and contracts, and close new business with brands, agencies, and studios. Expand accounts after initial wins while helping develop the company’s sales playbook, case studies, sequences, and processes. This is an on-site, full-cycle new-business role collaborating closely with founders and product teams.

Own technical relationships with strategic enterprise customers throughout Moveworks implementations. Design AI agent solutions, enterprise integrations, workflows, and automations using APIs, iPaaS tools, cloud functions, and scripting. Advise customers on agentic AI roadmaps, coordinate cross-functional delivery, develop reusable capabilities, and mentor engineers. The role combines solution architecture, hands-on implementation, technical consulting, executive communication, and up to 25% travel.

Lead enterprise go-to-market execution for Samsara’s AI products. Partner with account executives to develop strategic pipeline, architect complex deals, run high-touch pilots, define customer success metrics, and translate AI capabilities into measurable operational outcomes. The role requires selling complex enterprise solutions, navigating six- and seven-figure transactions, influencing multiple stakeholders, collaborating with product and GTM teams, and creating scalable sales frameworks for emerging AI offerings.

Manage strategic Payments AI transformation initiatives from initiation through delivery. Responsibilities include roadmap development, governance, cross-functional coordination, stakeholder alignment, risk management, success metrics, and delivery oversight with Product and Technology teams. The role leads complex change projects and supports the evolution of payments products through AI, data, cloud, and agile delivery practices.

Lead hands-on development of AI and machine learning solutions for asset and wealth management. Design scalable data pipelines, develop and productionize ML and LLM models, implement inference services, and deploy platforms to AWS or Azure. Collaborate with business, product, and technical teams while driving architecture, innovation, security, and adoption of shared AI capabilities.

Develop and operationalize advanced AI and machine learning solutions for financial risk management. Responsibilities include building multi-agent systems, orchestration layers, evaluation frameworks, drift monitoring, retraining processes, scalable data applications, and workflow integrations. The role partners with senior leaders and cross-functional teams to drive AI adoption, communicate insights, and deliver measurable business value. Candidates need enterprise-scale data science experience, production ML expertise, and multi-agent system development skills.

Leads enterprise sales for Uniphore Marketing AI, owning a direct territory while overlaying core sales accounts. Responsibilities include prospecting, executive-level selling to CMOs, positioning AI within Martech and CDP environments, building business cases, closing multimillion-dollar deals, forecasting, coordinating cross-functional teams, and shaping product strategy. The role involves 6–12-month sales cycles, eight-figure opportunities, and moderate domestic and international travel.

Leads the design, deployment, and operation of production AI/ML and LLM systems. Responsibilities include building data and ML pipelines, managing model registries and feature stores, developing CI/CD and experimentation frameworks, operating cloud training infrastructure, implementing observability and guardrails, and ensuring security, compliance, reliability, and performance. The role also guides architecture, incident response, governance, and cross-functional collaboration while mentoring engineers and transitioning models from research to production.

Build production AI/ML software for supercomputers and AI infrastructure, including anomaly detection, forecasting, root cause analysis, automation, and operational intelligence. Develop services with Go, Python, and React; integrate machine learning models, LLM workflows, agentic systems, and analytics. Own the lifecycle from data engineering and model development through deployment, monitoring, and improvement while collaborating with engineering, architecture, product, and customers.

Leads forward deployment of agentic AI systems within a business unit. Designs and delivers production LLM solutions, including integrations, RAG pipelines, prompt orchestration, multi-agent workflows, data engineering, and performance experiments. Measures ROI, improves data quality, mentors engineers, guides technical delivery, and communicates with business stakeholders. The role requires strong Python, cloud-native deployment, enterprise integrations, responsible AI, and data security expertise.

Design and build scalable AI-native developer platforms, backend services, APIs, frameworks, and modern frontend experiences. Improve engineering productivity through AI-powered workflows, automation, developer tooling, and SDLC integrations. Lead architecture decisions, mentor engineers, and drive reliability, scalability, performance, and observability across cloud-native distributed systems. Collaborate with product managers, architects, and engineering teams to deliver reusable platform capabilities and evaluate emerging AI technologies.

Leads cybersecurity architecture for cloud applications, AI/ML platforms, agentic systems, and MCP integrations. Defines secure reference architectures, controls, authentication, authorization, encryption, segmentation, and data protection requirements. Conducts threat modeling for risks including prompt injection, data leakage, model threats, and supply-chain exposure. Owns security design reviews, architecture governance, risk decisions, and stakeholder communication while developing software and validating AI-assisted security recommendations.