Top Artificial Intelligence Jobs

The Enterprise Architect will design scalable AI solutions, mentor teams, support business development, and manage client relationships while evolving technology practices.

As a Staff Software Engineer, you'll design, build, and test Gusto's core platform services, mentor engineers, and collaborate with various teams to solve complex engineering problems.

Design and build AI Gateway systems for high-volume, latency-sensitive inference at the edge. Implement APIs, routing, observability, controls, developer workflows and tooling. Prototype ambiguous ideas to production, improve reliability, performance, cost-efficiency and debuggability, and mentor engineers while dogfooding AI-native tools, agents, and automation to accelerate development and operations.

Lead and scale a field sales team focused on acquiring and expanding top-tier AI and digital-native enterprise accounts in the SF Bay Area. Own regional revenue targets, recruit and coach reps, act as executive sponsor for strategic accounts, advise CTOs/engineering on Cloudflare architectures (Workers AI, R2, network security), and partner cross-functionally to execute regional go-to-market strategies and close complex deals.

Lead design and delivery of enterprise integrations, automation, and AI-driven workflows across SaaS platforms. Architect scalable APIs, middleware, and conversational self-service experiences; partner with Security, Infrastructure, and Product; mentor engineers and drive long-term platform strategy, governance, and operational excellence.

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 and productionize agentic AI systems and components, improve agent behavior and reliability, create eval benchmarks and high-quality datasets, tune and evaluate LLMs and models, optimize latency and reliability in production, and partner with platform and UI teams to deliver end-to-end ML solutions.

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.

Lead Datadog's AI corporate development by sourcing startups, supporting acquisitions, investments, and partnerships. Drive diligence, valuation, financial modeling, and integration planning while collaborating with product and engineering and building relationships across founders and VCs.

Build, test, deploy, and document business process automations using Power Automate, Power Apps, SharePoint, and AI assistants. Map manual workflows, implement error handling, create training materials, measure automation impact, and support innovation projects. The six-month on-site internship includes collaboration with process owners, practical testing, troubleshooting, and research into automation tools.

Build, test, deploy, and document business automations using Power Automate, Power Apps, SharePoint, and AI assistants. Map manual processes, design logical workflows, handle errors and exceptions, create training materials, measure automation impact, and support internal innovation projects. The role includes collaboration with process owners, practical troubleshooting, research, and maintaining live automations used by internal teams.

Own product-layer performance for agentic AI systems in healthcare. Design prompting, retrieval, context, memory, tool use, evaluation, escalation, and human-review workflows. Build production-grounded evaluations, diagnose failures, improve accuracy, reliability, latency, cost, and steerability, and approve model changes. Partner with Product and Engineering while maintaining model cards, intended-use guidance, limitations, and failure-mode documentation for safe, transparent deployment.

Build and maintain production generative AI agents, LLM services, APIs, RAG pipelines, evaluation frameworks, and observability infrastructure. Develop intent recognition, query decomposition, context engineering, and self-service data capabilities. Integrate agents with internal and third-party systems, optimize latency and cost, automate business processes, and support AI-driven media planning and data monetization. Collaborate cross-functionally in an agile environment while adapting to evolving requirements.

Design and build end-to-end software primitives for AI infrastructure: domain modeling of power/datacenters/chips, authorization, audit, orchestration, vendor data ingestion (KMZ/BIM/Revit), and agent integration to enable safe, auditable agent operators. Ship production-quality systems and work across ambiguity to turn unstructured data into durable, composable entities.

Build and deploy production generative AI and agentic systems for enterprise clients. Responsibilities include identifying high-value problems, shaping architecture, developing multi-agent workflows, APIs, data pipelines, integrations, and distributed systems, and owning deployments through measurable impact. The role requires hands-on ownership of evaluation, observability, security, reliability, scalability, latency, and cost, along with direct collaboration and communication with senior client stakeholders.

Own the full product loop: identify high-impact problems, rapidly prototype and ship AI-accelerated solutions, build internal tools and automations, collaborate with operations and business teams, and iterate based on usage and data to drive adoption and business impact.

Design, build, operate, and maintain enterprise AI platform services and agent runtimes. Develop APIs, SDKs, MCP servers, tool interfaces, retrieval and embedding pipelines, model serving, evaluation infrastructure, and distributed data foundations. Establish engineering, security, testing, CI/CD, and infrastructure standards while optimizing platform cost and scale. Apply AI/ML capabilities to healthcare workflows, ensure PHI protection and tenant isolation, evaluate emerging technologies, and mentor engineers while influencing technical strategy.

Design and operate scalable batch and streaming data platforms supporting machine learning and generative AI. Build pipelines for structured, unstructured, OCR, document, and image data; develop RAG, semantic search, and LLM-powered solutions; and establish data quality, observability, governance, orchestration, and deployment practices. Partner with stakeholders, lead platform scalability and cost optimization, mentor engineers, and translate ambiguous needs into production-ready technical roadmaps while securely handling sensitive data.

Develop and deploy practical AI solutions across internal tooling, AI platforms, and existing products. Build LLM applications using prompt and context engineering, RAG, agentic workflows, and generative AI. Create evaluation frameworks, benchmarks, testing harnesses, and production infrastructure. Apply machine learning algorithms, contribute to secure AWS-based architecture and DevOps, collaborate with product and engineering teams, and mentor junior engineers.

Leads IREN’s global supply chain systems modernization and AI enablement strategy. Owns the ERP, PLM, planning, analytics, and application portfolio roadmap; builds a supply chain systems program management team; establishes data governance and system resiliency; implements S&OP and IBP capabilities; advances predictive analytics; deploys AI/ML and automation use cases; and manages implementation partners. The role partners extensively with executive and cross-functional stakeholders across supply chain, engineering, finance, legal, and IT.

Leads enterprise AI strategy and product management across PayPal’s highest-priority initiatives. Establishes product vision, strategy, customer-focused requirements, analytics, and operating mechanisms that improve efficiency, visibility, and outcomes. Partners with cross-functional stakeholders and senior leadership, influences architectural roadmaps, balances regulatory and business considerations, oversees product profitability, and scales AI capabilities. The role also supports AI governance, model risk management, and responsible AI practices in a regulated fintech environment.

Develops and operationalizes AI and data governance policies, standards, procedures, checklists, decision trees, and reporting templates. Translates frameworks including NIST AI RMF, the EU AI Act, and Colorado ADMTA into practical workflows. Partners with engineering, data science, product, governance, risk, and business teams to test standards, define metadata and logging requirements, and enable cross-functional execution through version-controlled policy frameworks.

Secure LLMs, generative AI systems, ML infrastructure, training pipelines, and AI applications. Responsibilities include threat modeling, architecture reviews, security controls, hardening, vulnerability remediation, data privacy, incident response runbooks, vendor reviews, governance, policy development, and AI security training. The role also supports proof-of-concept security solutions and monitors emerging AI threats.

Leads the Solutions Architecture team supporting Cloudflare’s AI and Developer Platform. Develops technical sales strategy, drives pipeline and revenue, manages people and budgets, advises sales leadership, engages executive customers, collaborates with Product and Marketing, and establishes customer feedback loops to improve product strategy and adoption.

Conduct AI security research, agentic and LLM testing, vulnerability discovery, adversary simulations, and full-chain red team operations. Test WAF, EDR, and SIEM detection efficacy using MITRE ATT&CK, collaborate with blue teams and incident response, develop detection validation frameworks, report risks to executives, and mentor security professionals.