Top Artificial Intelligence Jobs

Leads financial reconciliations, variance analysis, financial controls, audit coordination, and remediation for Finance transformation initiatives. Reviews AI- and automation-assisted outputs for accounting accuracy, ensures alignment with control frameworks and data integrity standards, and manages exceptions and audit-ready documentation. Partners with Finance leadership, auditors, and cross-functional teams while supporting the adoption of AI and automation across Finance processes.

Leads full-cycle talent acquisition across creative, media production, and technical roles. Responsibilities include developing recruiting strategies, managing and mentoring recruiters, sourcing candidates, overseeing hiring processes, tracking recruitment metrics, managing recruiting technologies, ensuring employment-law compliance, negotiating offers, and partnering with leadership to scale hiring capacity and improve candidate experience.

Own the strategy, design, development, and deployment of AI safeguards systems and product experiences across Anthropic’s products and cloud platforms. Define safety-by-design approaches, develop evaluations and risk metrics, prioritize roadmaps, make technical tradeoffs, and collaborate with policy, research, engineering, enforcement, and product stakeholders to mitigate deployment and user risks.

Lead AstraZeneca’s AI research agenda for clinical development across oncology and biopharmaceuticals. Develop methods for treatment-effect heterogeneity, biomarker discovery, patient stratification, survival analysis, and trial generalization. Design and evaluate agentic AI systems using Python and modern machine-learning frameworks. Establish reproducible engineering, responsible AI governance, and regulatory-aligned evaluation practices while influencing clinical strategy and mentoring scientists and engineers. Disseminate findings through publications, patents, partnerships, and conferences.

Develop and integrate intelligent feature layers for Workday’s AI agents. Build production-grade LLM applications using RAG pipelines, orchestration frameworks, prompt engineering, APIs, vector databases, semantic search, and data pipelines. Partner with engineering, product, and UX teams to deliver reliable, user-focused AI features embedded in Workday’s platform. Responsibilities include backend development, testing, deployment, data integration, and continuous optimization of agentic workflows.

Build and operate partner integrations enabling secure agent experiences across web applications, APIs, connectors, CLIs, and MCP servers. Responsibilities include architecture, coding, identity and OAuth debugging, evaluations, launch readiness, staged rollouts, observability, incident investigation, and platform improvements. The role requires close collaboration with external engineering teams and internal product, security, legal, and go-to-market stakeholders.

AI Engineering Intern supporting the design, development, testing, and responsible use of AI-enabled solutions. Responsibilities include coding, data preparation, AI prototyping, automation, cloud and platform support, testing, documentation, governance, and communicating technical findings. The 10-week, full-time hybrid internship runs from June through August in Reston, Virginia, with in-person work twice weekly.

Supports rapid AI prototype development using AI tools and frameworks, building lightweight front-end and back-end interfaces, designing prompts, applying responsible LLM grounding techniques, and integrating and testing capabilities in real workflows. Collaborates with senior engineers and technology partners, learns emerging AI technologies, and may present deliverables to leadership. This is a full-time, 10-week hybrid internship in Reston, Virginia.

Leads the architecture and operationalization of enterprise AI platforms, including MLOps/LLMOps, model lifecycle management, observability, governance, Responsible AI, and GenAI orchestration. Makes platform-level technical decisions, evaluates emerging technologies, guides model and architecture selection, and develops enterprise AI roadmaps. Partners with business, data, technology, and platform teams to deliver scalable production solutions while mentoring cross-functional teams and supporting AI Centers of Excellence.

Lead Engine’s internal AI Platform organization and technical strategy. Own the LLM gateway, agent frameworks, evaluation systems, developer-experience tooling, automation APIs, RAG and agent data infrastructure, observability, security, and cost controls. Build the initial platform hands-on, establish a unified enterprise AI stack, partner with Applied AI and Workforce Transformation leaders, and scale the organization through senior engineering leadership. Drive the Velocity program toward increased delivery autonomy and adoption across engineering.

Leads enterprise lending strategy across CRE and SBA 504 platforms, overseeing loan origination, structuring, portfolio growth, credit risk, regulatory compliance, and governance. Partners with executive leadership, the Board, capital providers, and banking affiliates while developing lending programs and managing high-risk credits. Builds high-performing sales and lending teams, promotes responsible AI adoption, and ensures portfolio performance, profitability, and regulatory standards.

Own enterprise product strategy and customer outcomes for Lightning AI's AI infrastructure platform. Identify high-value opportunities, translate technical user needs into product requirements, remove adoption blockers, and partner with Engineering, Sales, Customer Success, Marketing, and Design. Drive integrations, APIs, workflows, instrumentation, and enterprise expansion while coaching engineering teams and delivering intuitive products for developers.

Research and prototype transformer-based and graph-based foundation models using customer, transaction, and merchant data. The intern will design and train models, run rigorous experiments, evaluate results, and develop working prototypes. Responsibilities include collaborating with Product, Engineering, Analytics, and Applied Science teams to improve customer experience, operational efficiency, and business outcomes.

Own the vision, roadmap, requirements, and delivery of conversational AI features. Translate customer feedback, research, and market intelligence into product priorities, PRDs, success metrics, and high-quality experiences. Lead cross-functional teams, coordinate dependencies, support enterprise pilots and go-lives, and guide AI evaluation, testing, telemetry, quality, and performance. Drive capabilities including clarification, multimodal experiences, information collection, feedback intelligence, and error handling across AI orchestrators.

Owns the vision, roadmap, requirements, and customer outcomes for conversational AI features. The role guides AI experience strategy, prioritizes feature gaps, translates customer feedback into product improvements, creates PRDs and success metrics, and coordinates engineering, design, and cross-functional teams. Responsibilities include AI evaluation, telemetry, quality and performance requirements, usability research, strategic customer pilots, go-lives, escalations, and end-to-end delivery of conversational AI capabilities.

Develop and maintain enterprise cybersecurity strategy, roadmaps, target-state architectures, and security standards. Advise executives and technical teams on cloud, data, AI, application, infrastructure, identity, privacy, and regulatory security. Lead secure AI strategy and governance, assess emerging threats and technologies, guide cybersecurity investments, and support transformation, modernization, and acquisition initiatives.

Lead the design and optimization of GPU-cluster infrastructure supporting AI and ML research. Partner with researchers, data engineers, and DevOps teams to identify bottlenecks, improve researcher efficiency, and build scalable, highly available systems. Drive infrastructure roadmaps, optimize resource utilization, define performance metrics, and oversee distributed training operations across HPC environments. The role requires deep expertise in accelerated computing, storage, scheduling, networking, containers, cloud platforms, and AI/ML frameworks.

Drive Foundation AI programs from kickoff through deployment and stabilization. Translate strategy into roadmaps, milestones, governance, risks, dependencies, and success metrics. Coordinate machine learning, data science, sensor intelligence, engineering, firmware, research, and product stakeholders. Support infrastructure planning, vendor tradeoffs, executive communications, decision-making, and process improvements to deliver reliable, scalable AI capabilities.

Build and manage Roboflow Labs’ frontier-lab business development pipeline. Own the full sales cycle, including outreach, discovery, evaluations, pricing, proposals, negotiation, procurement, legal coordination, and closing. Establish repeatable CRM, forecasting, pipeline-review, and account-planning systems while developing durable customer relationships. Represent Roboflow Labs at industry events and engage research scientists, human-data teams, technical executives, procurement, and legal stakeholders.

Write and adapt technical and non-technical content across social media, blogs, founder communications, and company announcements. Translate research papers and technical findings into accessible writing, maintain distinct brand and founder voices, verify claims, collaborate with stakeholders, repurpose content across channels, and independently manage deadlines for a part-time contract.

Own Roboflow Labs’ contributor supply-side growth, managing the funnel from awareness and application through onboarding, activation, retention, and reactivation. Build acquisition channels, referral programs, partnerships, and expert contributor cohorts. Set compensation benchmarks, optimize incentives, and protect network quality through screening, fraud prevention, identity verification, and contributor experience improvements.

Leads presales discovery, solution architecture, technical proposals, workshops, and statements of work for digital and cloud transformation services. Partners with sales, delivery teams, clients, and technology vendors to develop solutions involving application modernization, AI, data platforms, and cloud technologies. Focuses on Retail or Manufacturing transformation, executive presentations, account leadership, go-to-market development, and mentoring others.

Build Trustible’s agentic AI infrastructure, including MCP tool integrations, AI agent data pipelines, and reliable backend platform features in Python and Django. Design scalable ingestion and processing systems, make architecture decisions, harden production systems, and establish engineering standards. Partner with the CTO on the agentic roadmap while mentoring engineers and balancing rapid delivery with long-term maintainability.

Owns large enterprise accounts, driving new business, adoption, expansion, and consumption revenue. Responsibilities include prospecting, executive engagement, complex deal strategy, technical evaluations, negotiations, forecasting, account planning, and guiding customers from AI discovery through deployment and sustained usage. Partners with engineering, solutions, procurement, and customer stakeholders to create measurable business outcomes and inform product and go-to-market strategy.

Leads enterprise adoption and governance of AI-enabled quality engineering and test automation. Develops reusable automation frameworks, standards, playbooks, and best practices; evaluates AI-assisted testing such as automated test generation, self-healing automation, risk-based testing, and defect analysis. Partners with engineering teams, mentors quality engineers, establishes KPIs, and supports cloud, DevOps, Agile, and CI/CD testing practices across UI, API, integration, and headless applications.