Top Artificial Intelligence Jobs

Own the strategy and roadmap for AI detection and discovery products, creating inventories of models, applications, agents, and AI-enabled features. Lead distributed engineering, design, data science, and research teams; define detection taxonomy, coverage, precision, recall, and quality standards; guide integrations and partnerships; engage customers and executives; and translate AI governance regulations into product requirements. Mentor product managers and serve as the subject matter expert for AI deployment and detection.

Develop and execute global direct-to-consumer strategies spanning digital marketing, e-commerce, SEO, CRM, content, UX, and AI-enabled production. Build customer acquisition, engagement, retention, segmentation, personalization, and marketing automation programs across multiple brands and markets. Integrate digital initiatives with physical brand experiences, establish scalable roadmaps, optimize performance using analytics, and promote digital, CRM, and AI best practices across the organization.

Design and deliver enterprise AI solutions using agentic AI, LLMs, NLP, RAG, multi-agent systems, and tool orchestration. Partner with stakeholders to identify high-value use cases, define success metrics, and focus on business outcomes. Build scalable, reliable, explainable, and governed systems with evaluation, monitoring, and guardrails. Advise teams on responsible AI adoption, contribute to strategic best practices, and mentor colleagues.

Develops advanced machine learning, deep learning, signal processing, optimization, and numerical modeling algorithms for biomedical signals and next-generation medical devices. Responsibilities include algorithm design, implementation, testing, documentation, data analysis, disease detection and prediction modeling, patentable innovation, and collaboration with hardware and software engineering teams.

Develop AI/ML algorithms and ETL infrastructure for LLM, NLP, and time-series solutions. Build scalable data pipelines, curate evaluation datasets, implement machine learning models, optimize data delivery, automate processes, and develop software using Agile methodologies. The role collaborates with researchers and developers and may involve cloud services, distributed computing, containerization, GenAI operations, reinforcement learning, and GPU-based algorithm implementation.

Develops AI/ML algorithms and ETL infrastructure supporting LLM, NLP, predictive analytics, and other customer solutions. Builds and maintains data pipelines, curates evaluation data, improves scalability and automation, and collaborates with researchers and developers using Agile methods. The role requires Python-based data engineering, machine learning experience, and an active TS/SCI clearance, with preferred experience in cloud, containers, distributed computing, reinforcement learning, GenAI operations, and GPU programming.

Design, develop, and deploy production-grade AI/ML solutions for national security missions. Build NLP, LLM, computer vision, deep learning, and generative AI models; scalable data pipelines; APIs; microservices; and cloud or edge-deployed services. Optimize, version, evaluate, and monitor models while integrating them into secure operational environments. Collaborate with engineers, mission experts, and product teams to define requirements, document designs, and deliver reliable AI capabilities.

Designs, develops, deploys, and integrates production-grade AI/ML systems for national security missions. Responsibilities include building NLP, LLM, computer vision, and deep learning models; developing scalable data pipelines, APIs, microservices, and cloud or edge services; optimizing and evaluating models; and applying MLOps, security, reliability, and software engineering practices. The role collaborates with mission experts and engineering teams and requires an active TS/SCI clearance.

Own the sales pipeline from prospecting and inbound demos through follow-up, virtual product demonstrations, objection handling, negotiation, and closing. Maintain accurate CRM records, nurture warm leads through calls, emails, texts, and LinkedIn, and collaborate with senior sales leaders to meet revenue targets. The role requires SaaS sales experience, strong communication, organization, resilience, customer curiosity, and consistent goal achievement while working Pacific Standard Time hours.

Build modular AI video-generation pipelines for mobile gaming advertisements. Integrate generative image, video, text-to-speech, and talking-head models; orchestrate fal.ai jobs with retries, webhooks, rate limits, resumability, and cost tracking. Use FFmpeg to assemble clips, subtitles, overlays, audio, and multiple aspect ratios. Document configurable workflows so marketing teams can operate them without coding, while collaborating with creative specialists and demonstrating a working pipeline.

Lead strategy, roadmap, and scaling of enterprise AI/ML platforms (including GenAI and agent frameworks). Enable cross-functional teams to build, deploy, govern, and operate production-grade AI solutions; define architecture and guardrails; track adoption, reliability, cost, and developer productivity; partner with Security, Privacy, Cloud, and vendor partners; and drive platform delivery through agile execution.

Develop AI and machine-learning software on an agile Scrum team supporting mission-critical systems. Apply optimization, signal processing, control theory, probabilistic modeling, neural networks, classification, and dimensionality-reduction techniques. Program primarily in MATLAB, Python, or R, use Git for version control, and potentially deploy solutions with Docker, Kubernetes, Linux, embedded systems, and GPU programming. The role is fully onsite in Morrisville, North Carolina, follows a 9/80 schedule, requires U.S. citizenship, and requires obtaining a Top Secret/SCI clearance with a counterintelligence polygraph.

Develop AI and machine learning software on an agile Scrum team supporting mission-critical systems. Apply optimization, signal processing, control theory, probabilistic modeling, neural networks, classifiers, and dimensionality reduction. Build and deploy algorithms using high-level programming languages, version control, and potentially containerized, distributed, embedded, GPU-enabled environments. The role is fully onsite in Morrisville, North Carolina, with a 9/80 schedule and approximately 10% travel.

Leads enterprise technology, architecture, and AI strategy across transformation initiatives. Defines technical roadmaps, architectural standards, governance frameworks, reference architectures, and responsible AI practices. Evaluates emerging technologies, drives proofs of concept and modernization, aligns investments with business priorities, and accelerates AI adoption. Partners with executives and cross-functional leaders, influences technical direction without direct authority, mentors senior engineers and architects, and represents the organization as a technology and AI thought leader.

Advise governments, AI Safety Institutes, and multilateral institutions on frontier AI capabilities, risks, evaluation, and adoption. Develop demos, pilots, prototypes, and evaluation suites; lead technical onboarding, workshops, architecture, and Claude integrations. Collaborate with policy, product, research, and engineering teams to design safe, reliable solutions for public missions, including cybersecurity. Build international partnerships and communicate complex AI concepts to technical and non-technical stakeholders.

Legal Counsel will support US expansion by negotiating complex B2B SaaS agreements, advising AI and engineering teams on product risks, managing privacy and security compliance across jurisdictions, and developing scalable legal policies and processes. The role partners with executive leadership and addresses novel generative AI legal issues in a fast-growing technology startup.

Owns business analysis, requirements, testing, governance, roadmap planning, and adoption for internal systems, AI, and automation initiatives. Leads discovery, translates needs into development-ready requirements, coordinates testing and delivery, evaluates AI opportunities, tracks outcomes, and presents recommendations to executives. Partners with engineering, data science, and business teams to prioritize initiatives, build business cases, manage dependencies, and improve product governance practices.

Leads commercial demand, revenue, patient-flow, and launch forecasting across an oncology and cell therapy portfolio. Builds patient-based and epidemiology-driven models, develops the commercial AI roadmap, and creates compliant AI-powered systems for analytics, reporting, market research, competitive intelligence, and commercial operations. Evaluates AI vendors and build-versus-buy options while translating complex quantitative insights into recommendations for senior stakeholders.

The Director, Search & AI Visibility leads integrated paid search, SEO, and answer engine optimization across healthcare and academic properties. Responsibilities include developing search economics and attribution models, owning technical SEO and content strategy, measuring AI visibility and citations, advising on paid campaigns and budgets, managing vendors and platforms, building a search and AI visibility team, and partnering with IT, security, clinical, compliance, and leadership stakeholders. The role also establishes enterprise standards, accessibility and privacy practices, experimentation programs, and AI adoption capabilities.

Technical authority for partner-facing Workday AI platform and integration architecture. Design reference architectures, agent orchestration and governance, and integration patterns. Enable GSI technical teams via deep technical training, demo readiness, code accelerators, and playbooks. Translate roadmap into partner implications and represent Workday in joint technical forums while coordinating with Forward Deployed and Solution Architecture teams.

Serve as primary legal counsel for Unity’s AI products, advertising monetization, data rights, identity frameworks, and privacy matters. Counsel product, engineering, and data-science teams; draft and negotiate technology, partnership, research, and data-sharing agreements; establish positions on AI, intellectual property, privacy, and emerging regulation; and create scalable legal templates, playbooks, and guidance.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Designs and operates secure, scalable cloud infrastructure for AI/ML workloads across hybrid, multi-cloud, multi-enclave, and classified environments. Responsibilities include AI-optimized compute, networking, storage, Kubernetes orchestration, Infrastructure as Code, DevSecOps automation, cloud-native security, data and model governance, high availability, and integration with on-premises systems and GPU hardware. Requires collaboration across teams and active Top Secret clearance.

Build and deploy agentic AI applications, document-intelligence pipelines, retrieval-augmented systems, and workflow automation for pharmaceutical sourcing and supply-chain decisions. Develop reliable agent skills, evaluations, guardrails, monitoring, and MLOps practices. Partner with sourcing, procurement, strategy, and technology teams to translate ambiguous business needs into production AI solutions, including the PRD Supply Chain Intelligence agent. Mentor colleagues and guide responsible AI adoption in a regulated environment.

Lead a unified product strategy across consumer, subscription, enterprise, and API offerings. Own activation, retention, pricing, packaging, upgrades, experimentation, metrics, and revenue planning. Build AI-agent workflows supporting product discovery, research, specifications, forecasting, and launches. Partner directly with the Founder, CEO, customers, and cross-functional teams to prioritize and deliver outcomes.