Top Artificial Intelligence Jobs

The Solutions Architect will implement ERP projects focusing on NetSuite integration, optimize functionalities, and ensure system reliability while collaborating with stakeholders.

Design and deliver AI solution architectures, build proofs-of-concept and pilots, partner with infrastructure, security, and service teams to operationalize AI solutions, establish reusable patterns and documentation, and support ethical, compliant deployment across cloud and on-prem environments.

The engineer will leverage AI to enhance pre-silicon verification processes, collaborate with teams, and improve methodologies using advanced tools.

Lead complex engineering projects focusing on safety and collaboration. Manage costs, schedules, and project documentation while ensuring teams communicate effectively. Participate in training and develop innovative solutions for automation and engineering systems.

The Lead Data Scientist will oversee AI projects, mentor engineers, and develop systems for knowledge retrieval and analysis in defense. Responsibilities include guiding technical strategy, collaborating across teams, and championing AI innovations.

The Lead Data Scientist will lead AI solution development for National Security by driving projects, mentoring teams, and enhancing systems with advanced simulation and optimization techniques.

Lead and develop a team of Applied AI Engineers while remaining hands-on in production code. Own technical outcomes, architecture decisions, engineering standards, customer technical relationships, hiring, and delivery across ambiguous enterprise environments. Partner with engagement and growth leaders, provide deliberate coaching and feedback, support customer deployments, and translate field insights into improvements for Mosaic, the company’s AI deployment toolkit.

Design, deploy, operate, and support secure AI tools, gateways, integrations, and automated workflows. Manage model access, APIs, permissions, monitoring, audit records, testing, troubleshooting, releases, and documentation. Collaborate with engineering, cybersecurity, platform, product, and operations teams to improve AI assistants, prompts, and workflow reliability. Contribute to cyber operations, technical planning, code reviews, and agile delivery while mentoring junior team members.

Support the deployment, operation, integration, and troubleshooting of AI tools, gateways, and automated workflows. Build secure API and enterprise-system connections, develop scripts and documentation, manage access and logging, monitor operational health, assist with cyber operations, and improve AI prompts and configurations. Collaborate with engineering, cybersecurity, product, and platform teams in an agile environment while communicating technical risks, issues, and recommendations.

Productionize detection, tracking, and vision-language models across edge devices and cloud infrastructure. Build evaluation systems, data feedback loops, deployment pipelines, and production metrics; optimize inference cost and performance; run staged rollouts and experiments; and ship customer-facing features connecting inference services, APIs, and product behavior.

Designs, administers, troubleshoots, and improves enterprise identity, AI, and multi-cloud infrastructure platforms. Responsibilities include managing Microsoft Entra ID, authentication, access controls, AI platform governance, Azure/AWS/GCP services, infrastructure automation, monitoring, security, compliance, migrations, and operational resilience. The engineer collaborates with cybersecurity, development, data, and infrastructure teams while independently supporting assigned platforms and developing automation using PowerShell, Microsoft Graph, and cloud-native tools.

Develops cost transparency, dashboards, forecasting, budgeting, governance, and optimization strategies for AI and machine learning workloads. Partners with engineering, data science, finance, procurement, security, and risk teams to improve cloud and vendor spend, GPU utilization, model deployment efficiency, and responsible AI adoption. Automates cost management using scripting, infrastructure-as-code, and cloud-native tooling while evaluating hosted, internal, and open-source AI platforms.

Lead Anthropic’s AI for Science program by developing partnerships with academic labs, startups, and foundations across biomedical science, chemistry, and materials science. Manage API credit strategy, partner onboarding, deployment plans, timelines, resources, reporting, and ecosystem insights. Coordinate with technical, product, and go-to-market teams; support technical prototyping; build scientific communities of practice; establish a research agenda; identify public-good opportunities; and represent Anthropic at scientific conferences.

Leads global marketing planning, investment allocation, capacity modeling, and target setting. Builds and manages a new team while redesigning marketing workflows for AI and agent-based execution. Drives organization-wide adoption, establishes standards for prompts and context, and implements AI governance around quality, risk, privacy, and responsible use. Partners with Marketing, Finance, Sales Strategy, and data and platform teams to improve pipeline efficiency, time to market, and growth across business units.

Partner with startup founders and engineering teams to architect, evaluate, deploy, and scale LLM-powered applications on the Claude Developer Platform. Serve as a trusted technical advisor throughout customer adoption, lead technical evaluations, demonstrate AI product capabilities, and guide architecture decisions. Collaborate with sales, product, and engineering teams, share startup use-case insights, and travel to customer sites and industry events.

Lead strategic quality and compliance initiatives for a greenfield aseptic drug product site. Serve as site SME for digital regulatory requirements, drive QMS and Data Integrity programs, perform risk assessments, support inspections and health authority engagement, and partner cross-functionally to embed a risk-based quality culture and continuous improvement.

Lead technical strategy with channel partners across ASEAN to design, validate, and scale Microsoft Cloud and Data & AI solutions. Drive offer development, run workshops and POCs, enable specializations, and translate technical work into repeatable, revenue-generating partner services aligned to Microsoft Cloud and AI priorities.

Support high-velocity B2B sales through outbound campaigns, event follow-up, conference preparation, stakeholder mapping, and demand conversion. Develop opportunities with legal and business stakeholders, master AI Enablement offerings, participate in client conversations, and partner with Sales Leads through qualification, proposals, and closing. Share market insights to improve messaging and sales strategy while progressively taking ownership of sales activities and deals.

Lead and grow a sales pod while personally developing and closing enterprise opportunities for Factor’s AI Enablement offerings. Build a repeatable GTM motion, sales playbook, messaging, demos, qualification processes, proposals, and coaching rhythms. Sell AI-enabled legal transformation solutions to senior legal, legal operations, procurement, transformation, and business stakeholders. Use buyer feedback to improve positioning, packaging, product modules, and go-to-market strategy while owning individual and team results.

Develop and productionize GenAI applications for federal-sector customers, including RAG, multi-agent systems, Text2SQL, and fine-tuning solutions. Advise customers, lead production rollouts, present technical concepts, collaborate with product and engineering teams, and influence the AI product roadmap. The role requires production machine learning deployment experience, strong data science expertise, customer-facing communication, U.S. citizenship, Secret clearance eligibility, and periodic customer travel.

Own product areas for an AI-powered neobank across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; and use research, feedback, experiments, and performance data to drive continuous product improvements.

Own AI Investing product areas across financial services, defining user problems, product direction, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use research, feedback, experiments, and performance data to launch quickly, monitor outcomes, make trade-offs, and drive continuous improvements.

Participate in a two-year international rotation program across R&D teams, developing AI and software solutions for network testing and communications technologies. Build clean, tested Python code; work with LLMs, APIs, orchestration frameworks, and agentic AI; apply ethical and safe AI practices; collaborate in Agile teams; and rapidly learn new technologies while contributing to product development and issue resolution.

Manages and optimizes paid search, paid social, display, and other digital campaigns to drive patient acquisition and measurable growth. Partners with agencies and internal web, content, SEO, and email teams on strategy, budgets, reporting, landing pages, UX, and conversion optimization. Analyzes performance data and AI-assisted insights, monitors AI-driven search trends and GEO developments, and recommends responsible improvements to maintain healthcare brand visibility and engagement.

Build and maintain Go-based backend services and APIs on AWS for agentic AI workflows, including metadata suggestions, automated ownership reassignment, system deprecation, and agent/MCP inventory. Design database schemas and queries in PostgreSQL and MongoDB, integrate asset discovery tooling, map dependencies and user journeys, and refactor legacy code safely. Deliver tested features through Agile/Scrum while collaborating with program and customer teams.