Top Artificial Intelligence Jobs

Build and deploy applied AI systems across Crunchyroll by embedding with business teams, identifying high-value workflow opportunities, and translating ambiguous problems into reliable technical solutions. Develop agents, RAG systems, automations, integrations, evaluations, observability, guardrails, and human-in-the-loop workflows. Measure business impact, collaborate with technical and business stakeholders, and create reusable components and patterns for scalable AI adoption.

Build and deploy applied AI solutions across Crunchyroll by embedding with business teams, identifying high-value workflow opportunities, and delivering reliable agents, automations, RAG systems, and integrations. Responsibilities include architecture, prototyping, production engineering, evaluations, observability, security, human-in-the-loop controls, stakeholder alignment, adoption, and reusable platform components. The role requires balancing rapid experimentation with scalable, maintainable production systems and measuring business impact after launch.

Build and deploy AI systems for startup customers, from initial implementation through ongoing adoption. Identify high-impact AI use cases, develop LLM applications and integrations, collaborate with customer engineering teams, and translate field insights into product roadmap improvements. The role requires strong Python or TypeScript skills, production AI experience, customer-facing communication, autonomy, and comfort working in ambiguous environments.

Lead the design, development, and deployment of production-grade AI applications, including LLM workflows, RAG systems, and agentic solutions. Establish AI engineering standards, architecture practices, observability, governance, security, and risk controls. Build automation and secure Python services, evaluate vendors and emerging technologies, and partner across product, engineering, legal, and risk teams. Mentor teams through documentation, workshops, and technical reviews while delivering reliable, scalable, cost-effective AI capabilities.

Leads the design and implementation of AI-powered finance workflows, agents, copilots, and integrations across ERP, billing, procurement, and other financial systems. Establishes AI architecture, governance, security, observability, and responsible-use standards while partnering with Finance, IT, Security, Legal, and Audit. Identifies automation opportunities, measures business impact, builds reusable frameworks, and enables nontechnical teams to adopt AI solutions.

Leads the design and implementation of AI-powered Finance workflows, agents, copilots, and integrations across ERP, billing, procurement, and related systems. Establishes AI architecture, governance, security, testing, observability, and responsible-use practices. Partners with Finance, IT, Security, Legal, and Audit to identify automation opportunities, define success metrics, build reusable frameworks, and enable nontechnical teams. Requires technical leadership, enterprise financial systems integration, LLM experience, and the ability to build scalable 0-to-1 solutions.

Build and govern Compa’s secure AI foundation across identity, access, data, endpoints, SaaS, cloud, and networks. Secure non-human identities, agent access, data flows, AI integrations, and third-party models. Design controls for prompt injection, data exfiltration, excessive agency, OAuth abuse, and unsafe tool use. Implement logging, detection, enforcement automation, and enterprise security architecture while partnering with technical, legal, privacy, and business teams.

Leads venture investment sourcing, evaluation, diligence, and execution across Seed through Series B. Drives company-wide AI and machine learning initiatives, maintains portfolio relationships, and develops executive, Board, and Investment Committee recommendations. The role requires technical fluency in AI or semiconductors, financial acumen, senior stakeholder influence, strategic judgment, team mentorship, and the ability to operate effectively in ambiguous, fast-paced environments.

Leads a new data science team developing AI and agentic-system evaluations for insurance pricing applications. Sets strategy, defines evaluation metrics and experiments, measures AI value and risk, partners with technical and pricing teams to deploy high-value solutions, and assesses third-party AI vendors. Requires strong people leadership, insurance pricing-model expertise, statistical and experimental-design skills, and hands-on experience with LLMs, RAG, and AI application development.

Own four to six monthly data studies using proprietary checkout and shopping data. Responsibilities include querying BigQuery with SQL, validating statistical methodology, conducting interviews and shopper research, writing publishable studies, maintaining canonical statistics, and developing story pitches for journalists and AI answer engines. The role directs AI agents, verifies their outputs, and collaborates with the Head of Search Product in a hybrid Santa Monica environment.

Owns major product roadmap components and strategic initiatives for software applications. Defines product outcomes, writes epics, features, and user stories, partners with engineering and UX, leads Agile delivery, coordinates client support, manages release plans, develops training and support materials, and applies user acceptance testing and AI/ML workflow knowledge.

Tutor Intelligence invites candidates to submit general applications for opportunities involving robot design, AI, manufacturing, deployment, fleet maintenance, sales, and scaling operational processes. Applicants should demonstrate work, ownership, curiosity, adaptability, collaboration, discipline, and communication. A LinkedIn profile is required, along with a resume and optional portfolio, GitHub, papers, or PDFs describing desired projects and ideas.

Drives exploratory sales and dealmaking, coordinates customers, partners, investors, vendors, and technical teams, and advances strategic projects across commercial and product domains. The role requires clear written communication, opportunity framing, stakeholder management, structured follow-through, and the ability to turn ambiguous ideas into concrete next steps.

Leads Microsoft Security’s portfolio narrative and strategy, translating complex security and AI innovations into compelling customer and market stories. Develops messaging, content, visual assets, campaigns, launches, events, and executive communications. Coordinates product marketing subject-matter experts, facilitates cross-functional decisions, partners with go-to-market teams, and activates narratives across digital and field channels. Establishes stakeholder alignment, content review, and executive engagement processes.

Designs and runs safety evaluations for advanced AI models, including benchmarks and test environments for reward gaming, sabotage, deception, capability improvement, and constraint violations. Reviews model trajectories, experiments, and failures; audits evaluations for contamination and weak grading; collaborates with engineers on reproducible scoring environments; and publishes benchmark releases, research reports, and recommendations.

Plans and integrates cyberspace operations for USCYBERCOM-supported missions. Develops OPLANs, OPORDs, FRAGOs, concepts of support, courses of action, crisis plans, and operational guidance. Leads joint planning teams, targeting synchronization, intelligence integration, capability assessments, and transition to current operations. Applies cyber threat knowledge, networking fundamentals, relevant laws and policies, and Joint planning doctrine while coordinating across DoD and Intelligence Community organizations.

Provides legal counsel on global privacy, cybersecurity, and AI governance. Advises stakeholders on regulatory compliance, reviews AI use cases, manages privacy assessments and third-party risk, negotiates data agreements, develops compliance frameworks, delivers training, coordinates cross-functional projects and outside counsel, and responds to regulatory inquiries.

Lead integration of autonomy components into reference implementations and deployable stacks. Develop C++ and Python tooling, software-in-the-loop and hardware-in-the-loop tests, platform integration layers, automated fixtures, and troubleshooting workflows. Investigate cross-system failures, support deployment to representative hardware, collaborate on flight testing, analyze integration issues, and create documentation and training materials. The role spans perception, localization, planning, real-time systems, and safety-critical autonomous platforms.

Designs and executes compliance, validation, and reliability tests for HPC-AI mechanical and thermal hardware, electronics enclosures, and production tooling. Responsibilities include testing tolerances, form/fit/function, shock and vibration, electromagnetic interference, safety, acoustics, system power, and thermal performance. The role collaborates with internal and outsourced engineering partners to develop reliable, cost-effective hardware solutions and applies mechanical design, CAD, CFD, and analytical problem-solving skills.

Supports the design, integration, deployment, troubleshooting, and continuous improvement of automated electrical, instrumentation, and test systems across manufacturing and laboratory environments. Partners with equipment suppliers and cross-functional teams on requirements, procurement, installation, qualification, data exchange, and root-cause analysis. Applies testability, manufacturing, instrumentation, networking, and data technologies to improve quality, productivity, and cost performance. Provides technical guidance and supports standardization across manufacturing test systems.

Manage and grow existing banking and financial services accounts through strategic relationship management, upselling, cross-selling, and account expansion. Engage senior client stakeholders, identify technology and consulting opportunities, lead proposals and negotiations, manage sales pipelines, and coordinate with delivery and presales teams. The role requires strong BFSI domain knowledge, IT services sales experience, and a proven record of expanding enterprise accounts and achieving revenue growth.

Advise clients on privacy, data protection, and responsible AI requirements. Evaluate AI systems for fairness, transparency, safety, privacy, accountability, and third-party risk. Develop governance operating models, policies, risk-tiering approaches, controls, impact assessments, and client deliverables. Interpret regulatory changes, support breach investigations, collaborate with legal, compliance, cybersecurity, data, and technology teams, and mentor junior staff. Apply technical literacy in AI/ML, GenAI, software development, technical architecture, and Python.

Supports financial crimes consulting engagements through research, data gathering, transaction and control analysis, regulatory risk assessment, and project coordination. Uses data analytics and AI tools to organize findings and prepare draft deliverables, presentations, status updates, and client discussion materials. Collaborates with project teams, tracks deliverables, reviews case documentation, and applies feedback while developing financial crimes compliance, risk management, and advisory skills.

Leads financial strategy for Azure networking infrastructure investments, including multi-billion-dollar capital allocation, capacity planning, business cases, scenario analysis, and investment frameworks. Partners with Engineering, Capacity Planning, and Sourcing to align network deployment with growth objectives. Provides executive insights on strategy, technology adoption, resource allocation, scalability, operational excellence, and return on capital.

Lead financial planning and decision support for cloud and datacenter engineering investments. Partner with engineering, talent acquisition, procurement, and finance stakeholders on FTE and vendor resource planning, forecasting, budgeting, workforce strategy, capacity investments, resource allocation, and financial analysis. Provide scenario modeling, business insights, trade-off recommendations, and executive-level reporting to support strategic engineering priorities and optimize resource deployment.