Top Artificial Intelligence Jobs

Leads global forward-deployed AI programs for J&J’s commercial strategy organization. Builds and scales production generative and agentic AI solutions, establishes technical standards, evaluation frameworks, deployment practices, observability, and compliance controls. Partners with business, technology, data science, regional, and vendor teams; manages and develops engineering talent; oversees AI use-case delivery, architecture, cost, quality, and adoption. Requires hands-on production LLM experience and leadership of forward-deployed engineering capabilities.

Design, evaluate, and deploy LLM-powered features end-to-end: prompt engineering, semantic retrieval, embeddings, vector stores, evaluation frameworks, and production integration while collaborating with product and engineering and working directly with users.

Own PlanetScale’s developer experience across AI coding tools, agent frameworks, MCP, CLI, APIs, and documentation. Build integrations, plugins, skills, demos, and agent-focused content; test workflows across leading AI clients; improve tool context and error handling; create agent evaluations and benchmarks; measure usage and recommendation accuracy; and communicate best practices through docs, blogs, videos, social media, and conferences.

Own HR systems, People analytics, reporting, dashboards, data governance, and AI-enabled insights. Partner with People Operations, Finance, Legal, Security, and business leaders to translate workforce questions into metrics and actions. Manage HRIS configuration, integrations, security, automations, data quality, system projects, and annual people cycles. Train managers and People teams while protecting employee data and delivering scalable self-service solutions.

Sell Qualitate’s AI-powered primary intelligence platform to private equity and growth equity firms. Own the full sales cycle, including prospecting, pipeline development, customized demos, trials, proof-of-concepts, negotiations, and closing. Build relationships with investment professionals and institutional buyers, develop vertical messaging and sales processes, provide product feedback, and help establish the company’s go-to-market function for the private equity segment.

Designs, develops, and supports enterprise AI applications, agents, and workflow automations. Builds Generative AI solutions using LLMs, prompt engineering, retrieval-based approaches, APIs, and enterprise data. Responsibilities include full software delivery, stakeholder collaboration, AI output evaluation, secure engineering, governance reviews, monitoring, risk controls, and operational support. The role requires strong software development experience, Python expertise, enterprise integrations, and understanding of responsible AI, security, privacy, and governance.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

Lead the architecture, development, deployment, optimization, governance, and observability of scalable AI platforms and systems. Build foundation model training, LLM inference, agentic workflows, similarity search, guardrails, and evaluation capabilities. Establish enterprise AI safety and transparency standards, drive long-term infrastructure strategy, mentor technical leaders, and guide organization-wide adoption of responsible AI solutions.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, scalability, and hardware utilization. Define reliability objectives, lead architecture and technical reviews, ensure security and compliance, contribute to long-term AI platform strategy, and mentor senior technical staff.

Develop and deploy advanced machine learning and data science solutions across large numeric and textual datasets. Partner with data scientists, engineers, and product managers to build customer-focused products. Lead model design, training, evaluation, validation, and implementation while researching emerging technologies and translating complex analyses into business outcomes.

Leads complex Finance transformation initiatives across teams, providing executive visibility, strategic communications, risk and dependency management, decision governance, planning, and reporting. Identifies and advances AI use cases to improve Finance workflows, automation, insights, and delivery effectiveness. Partners with business, technology, risk, and data stakeholders to drive consensus, adoption, and measurable outcomes.

Design, develop, deploy, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, collaborate across engineering and product teams, and mentor senior technical staff.

Design, develop, deploy, optimize, and support large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and orchestration pipelines. Lead cost-performance governance, technical design reviews, AI engineering standards, and long-term platform architecture. Apply state-of-the-art optimization techniques for latency, throughput, scalability, hardware utilization, and inference costs while mentoring senior technical staff and ensuring responsible AI practices.

Design, build, deploy, and support enterprise AI systems including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize model training and inference for scalability, cost, latency, throughput, and hardware utilization. Establish enterprise AI architecture standards, lead multi-cloud strategies, mentor engineering teams, promote responsible AI, and influence long-term technical roadmaps.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, agentic workflows, vector search, model evaluation, guardrails, and observability. Lead multi-model orchestration, cost-performance governance, technical design reviews, and AI platform roadmap development. Apply advanced optimization techniques to improve scalability, latency, throughput, hardware utilization, and inference costs while mentoring senior technical teams and promoting responsible AI standards.

Design, develop, deploy, and support large-scale AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, and hardware utilization. Architect multi-model orchestration pipelines, establish performance governance, lead technical design reviews, shape long-term platform strategy, and mentor senior AI engineering leaders.

Leads enterprise AI/ML architecture and engineering strategy, developing scalable AI-powered applications, agentic and generative AI solutions, streaming data pipelines, and cloud-native platforms. The role uses Python, Java, Spring Boot, Next.js, Kafka, and PostgreSQL while establishing architecture standards, governance, security, and reliability practices. Responsibilities include technical leadership across programs, stakeholder influence, mentoring engineering teams, evaluating emerging technologies, and driving responsible AI adoption.

Own the architecture and development of Klaviyo’s enterprise MarTech ecosystem, connecting marketing data, customer journeys, campaign execution, budgeting, and performance insights. Build AI-powered capabilities including generative AI, predictive scoring, and intent automation. Architect integrations across HubSpot, Salesforce, NetSuite, Coupa, and internal systems, advise on technical designs, support vendor evaluations, and partner cross-functionally to improve marketing efficiency and ROI.

Owns the enterprise architecture of Klaviyo’s marketing technology ecosystem, integrating HubSpot, Salesforce, NetSuite, Coupa, and internal systems. Designs AI-powered marketing capabilities including generative AI, predictive scoring, intent automation, personalization, and customer journey orchestration. Builds a centralized marketing hub spanning budgeting, planning, campaign execution, performance insights, and ROI measurement. Advises cross-functional teams on technical design, integrations, governance, vendor evaluation, and scalable architecture.

Leads the design and implementation of Zscaler’s AI-native talent operating system. Responsibilities include building enterprise talent intelligence, AI-powered skills profiling, internal talent marketplaces, career pathing, workforce mobility, succession planning, and talent architecture. The role partners with Talent Acquisition, HRBPs, People Technology, and People Strategy to translate workforce insights into development, leadership, performance, and retention initiatives.

Designs, operates, and improves enterprise AI platforms and integrations across Azure, Microsoft 365, Power Platform, and related technologies. Establishes governance, security, identity, deployment, observability, cost-management, and production-support standards for AI agents and generative AI solutions. Leads technical initiatives, develops reusable platform patterns, integrates enterprise systems, mentors engineers, and partners with cybersecurity, identity, architecture, legal, finance, and business teams to enable secure and reliable AI adoption.

Leads the Computer Vision Center of Excellence for Wind Engineering by establishing shared standards, platforms, dataset governance, model validation practices, and deployment architectures. Guides 2D/3D, multimodal, edge, cloud, and human-in-the-loop inspection solutions across industrial environments. Mentors practitioners, conducts technical reviews, manages model-risk practices, and translates computer vision performance into reliable engineering products and operational decisions.

Lead Anthropic’s state and local government affairs across Western states. Build relationships with legislators, governors’ offices, attorneys general, agencies, and local officials; track AI legislation and regulation; represent company positions; develop partnerships and policy campaign messaging; manage lobbyists and advisors; and coordinate with policy, communications, legal, and executive teams. Regular regional travel is required.

Lead product design workstreams for AI-powered features and experiences across native mobile applications and websites. Design high-fidelity, production-ready UI and UX artifacts while addressing AI edge cases, failure states, trust, and unexpected outputs. Collaborate with product, engineering, development, and clients; present to senior stakeholders; work within agile processes and enterprise design systems; and guide other designers.

Design and own developer infrastructure for isolated, production-like testing environments. Build CI/CD pipelines, deployment automation, build systems, realistic data and behavior simulation, and infrastructure supporting integration, load, performance, and correctness testing. Enable AI coding agents to test and validate code autonomously while improving engineering velocity, reliability, scalability, and cost efficiency. Partner closely with engineering teams to eliminate development bottlenecks.