Top Artificial Intelligence Jobs

Build and extend Skydio’s AI coding-agent platform, including agent integrations, MCP servers, sandboxed execution, secure permissions, secrets handling, and auditability. Develop infrastructure for internal tools and agents, collaborate with firmware, autonomy, cloud, and application teams to improve workflows, measure adoption and engineering impact, and drive internal adoption of AI development tools.

Leads enterprise data ingestion and integration for AI, machine learning, Generative AI, analytics, and BI workloads. Designs scalable pipelines for structured, semi-structured, unstructured, and multimodal data; establishes quality, governance, lineage, security, and observability standards; and supports RAG, AI Search, vector retrieval, and MCP capabilities. Partners with technical and business stakeholders, mentors engineers, evaluates emerging technologies, and drives production delivery and continuous improvement in a regulated financial-services environment.

Lead technical architect for data acquisition, processing, storage, analysis, and dissemination across defense programs. Translate sensor/telemetry into actionable information, define enterprise strategy, prioritize backlog, advise leadership, and ensure solutions meet operational needs while governing data standards and enabling cross-functional delivery.

Lead customer robot deployments from workflow discovery and site assessment through scoping, financial modeling, technical alignment, execution, acceptance testing, training, and handoff. Partner with engineering, research, safety, solution engineering, customers, and external teams to define requirements, success metrics, dependencies, and milestones. Translate field feedback into deployment practices while managing scope changes, implementation tradeoffs, customer value, utilization, and support needs.

Leads Covestro’s North American Digital and AI Centre of Excellence across Canada, the United States, and Mexico. Oversees regional AI and digital transformation programs, KPI performance, stakeholder adoption, team development, project portfolio governance, and budget management. Directs seven data scientists, project managers, analysts, and data engineers while coordinating global initiatives and aligning supply chain technology, analytics, automation, and AI efforts with global strategy.

Lead identification, development, and deployment of AI solutions across manufacturing and business operations. Prototype and implement generative AI, ML, computer vision, LLM-based assistants, and automation. Build Power BI dashboards and data models, integrate AI with ERP/manufacturing systems, and measure outcomes and ROI.

Lead enterprise AI deployments from business case through launch and expansion. Serve as the trusted contact for senior executives, translate customer needs into reusable platform capabilities, influence the product roadmap, prototype solutions, and develop business plans. Coordinate Product, Engineering, Sales, and Customer Success without direct authority. The role requires strong enterprise software experience, customer-facing leadership, hands-on execution, and the ability to operate in ambiguous environments.

Build and deploy applied AI solutions for R&D, including knowledge systems, generative AI, predictive models, intelligent automation, and decision-support tools. Develop data structures, semantic layers, metadata, retrieval mechanisms, and evaluation practices for reliable AI applications. Collaborate with R&D, IT, Information Security, Legal, and business stakeholders on responsible deployment, security, adoption, and measurable business impact.

Leads the architecture, development, deployment, and optimization of production-ready AI solutions combining graph databases, knowledge graphs, and LLMs. Acts as a trusted advisor to strategic customers, translating enterprise requirements into scalable Graph+GenAI applications. Responsibilities include stakeholder engagement, solution engineering, cloud deployment, data pipeline design, technical enablement, thought leadership, mentoring, and collaboration with product and marketing teams.

Build and operate production AI systems that transform written briefs into interactive web assets and personalized multimedia content. Responsibilities include agent orchestration, model selection, automated quality evaluation, generative video pipelines, recommendation and ranking integration, performance feedback loops, backend infrastructure, reliability tooling, and technical architecture. The role requires taking language-model and autonomous-agent systems from development through dependable production deployment at scale.

Supports vaccine technology development through AI and bioinformatics. Responsibilities include applying AI to vaccine candidate design, automating laboratory workflows, interpreting data, developing web applications and sequence-analysis tools, prototyping machine-learning algorithms, documenting regulated work, and completing an independent project. The intern will present results and contribute to continuous improvement in a startup environment.

Design, build, deploy, and scale production-grade AI agents and intelligent systems. Lead technical workstreams, develop agentic workflows, establish evaluation and monitoring practices, make engineering trade-offs, and partner with product and business stakeholders. Mentor engineers, conduct reviews, improve system reliability, evaluate emerging AI technologies, and transition successful solutions to long-term technology teams.

Design, build, and scale production-grade AI agents and intelligent systems from experimentation through deployment and support. Lead technical workstreams, develop agentic workflows, establish evaluation and monitoring practices, make architecture and model trade-offs, and create reusable AI engineering patterns. Partner with product owners and business stakeholders, mentor engineers, conduct design reviews, manage technical debt, and guide successful AI solutions toward long-term operational ownership.

Technical Writer responsible for creating, editing, and coordinating program documentation across cloud infrastructure, data and AI services, data visualization, and cybersecurity workstreams. The role includes producing security plans, ATO artifacts, system designs, architecture documents, SOPs, CONOPs, user guides, and customer deliverables; interviewing subject matter experts; coordinating document formatting and graphics; ensuring quality standards; and supporting standardized documentation processes.

Lead trust and safety for an AI mental-health product by developing policies, investigating risks and user reports, building response processes, and translating findings into product improvements. Collaborate with clinical, legal, research, engineering, and machine-learning teams. Communicate safety principles and evaluations internally and externally, establish benchmarks, manage sensitive cases, and continuously improve operational systems and policies.

Leads enterprise AI initiatives, technology programs, software development, Azure cloud operations, data warehouse architecture, integrations, and analytics enablement. Oversees .NET and Azure applications, ERP/CRM/payroll integrations, dimensional modeling, ETL pipelines, cloud governance, AI solution delivery, NetSuite optimization, Power BI adoption, and cross-functional performance improvement efforts.

Leads the architecture and strategic direction of generative AI platforms and software solutions. Designs AI agent reasoning, retrieval, enterprise integrations, authentication, testing, observability, safety guardrails, and production deployment practices. Provides technical leadership, reduces technical debt, supports automated workflows, and partners with business and executive stakeholders to deliver scalable, secure AI use cases.

Leads a global AI, analytics, and data organization supporting integrated supply chain processes. Owns the enterprise digital and AI roadmap, governed KPI products, data governance, self-service analytics, and the Heartbeat single source of truth. Manages leaders and technical teams, arbitrates KPI definitions, partners with senior stakeholders, and scales AI capabilities including predictive analytics, simulation, optimization, digital twins, generative AI, and agentic AI across a hub-and-spoke operating model.

Lead and scale Netskope’s North American Solutions Engineering organization across multiple countries. The role owns pre-sales methodology, technical win rates, sales partnership, talent development, operating models, executive customer engagement, and revenue-aligned execution. The VP will partner with Product, Engineering, Marketing, and Sales to strengthen cybersecurity positioning across SASE, SSE, ZTNA, cloud, data, and AI security. They will also drive AI, automation, and data-enabled productivity improvements while developing leaders and engaging senior customer executives.

Build and scale AI/ML solutions for healthcare revenue cycle automation. The role owns AI outcomes, identifies high-value use cases, shapes technical and product roadmaps, converts prototypes into scalable production systems, and architects infrastructure for training, testing, monitoring, security, and deployment. The engineer will apply ML, NLP, and LLM approaches to claims and workflow optimization while balancing technical tradeoffs, business value, cost, and operational efficiency.

Leads corrective action plans from healthcare regulatory audits, complaints, and compliance reviews through remediation, monitoring, validation, and closure. Partners with clinical, operational, compliance, and quality leaders to resolve barriers, assess risks, analyze trends, and sustain compliance. Develops dashboards and reports, facilitates root cause analysis and remediation meetings, supports audits, and identifies opportunities to automate workflows using AI and technology.

Leads enterprise AI strategy, consulting, solution design, development, integration, automation, governance, and adoption. Partners with business and technology leaders to identify opportunities, build agentic AI and generative AI solutions, integrate AI with enterprise systems, optimize workflows, and establish secure, scalable, responsible AI practices. The role includes technical leadership, discovery workshops, process assessments, stakeholder advising, platform evaluation, and oversight of AI initiatives across the organization.

Owns and prioritizes product backlogs, translates customer and business needs into technical requirements, facilitates Agile ceremonies, coordinates solutioning and dependencies, defines acceptance criteria, supports sprint planning, and partners with engineering, QA, architecture, and product management. The role also gathers feedback, evaluates delivery performance and adoption KPIs, drives demos and retrospectives, and adjusts future roadmap increments. Requires 5–7 years of product ownership experience in cloud or SaaS environments.

Freelance writers summarize recent machine learning research papers for The Batch, an AI newsletter reaching over two million professionals and students. Writers must understand machine learning technology, explain complex research clearly in an established format, and communicate effectively in English. The role is intended for graduate students and postdocs in machine learning, with negotiable freelance compensation.

Lead and mentor a small trade credit analytics team, oversee day-to-day trade credit operations, drive process improvements and controls, produce reports and insights, collaborate cross-functionally, and support team development and project execution to meet KPIs and SLAs.