Top Artificial Intelligence Jobs

Evaluate, configure, integrate, and develop AI and enterprise technology solutions for legal and business operations. Translate stakeholder needs into technical requirements, test applications and AI workflows, build prototypes, automate processes, develop API integrations, troubleshoot data flows, and support implementation. The role requires maintaining reliable, secure, scalable solutions while documenting findings and collaborating with legal, engineering, IT, security, data, and application teams.

Owns Takeda’s AI-native small-molecule discovery product family, including scientific vision, product strategy, roadmap, adoption, and value realization. Leads cross-functional teams across drug discovery, computational science, data, technology, and external partners. Defines AI-enabled workflows, priorities, KPIs, and technology direction while ensuring products meet scientists’ needs and deliver measurable scientific and business impact.

Leads Takeda’s AI-native Endpoint Generation product portfolio for drug discovery. Owns scientific vision, product strategy, roadmap, customer experience, adoption, KPIs, and business value. Partners with scientific, computational, data, technology, product, and external research teams to develop automated workflows for commissioning experiments and returning decision-ready data with protocols, metadata, and provenance. Provides strategic technology direction and drives cross-functional alignment across in vivo research, pharmacology, DMPK, safety, assay, and discovery teams.

Leads Takeda’s AI-native large molecule discovery product family, owning scientific vision, product strategy, roadmap, adoption, KPIs, and business value. Partners with scientists, computational teams, technology leaders, development squads, and external vendors to redesign biologics discovery workflows using AI, data, and automation. Provides portfolio-level direction, prioritizes capabilities, aligns stakeholders, guides technology choices, and drives measurable scientific and business impact across the biologics research organization.

Owns the strategic vision, roadmap, delivery, adoption, and business value of Takeda’s AI-native discovery automation and robotics product family. Leads cross-functional teams across scientific, digital, data, computational, automation, and technology functions; defines AI-enabled laboratory workflows; prioritizes investments; guides platform and integration choices; manages stakeholders and external partners; and drives measurable improvements in laboratory throughput, data quality, scientific impact, and operating efficiency.

Leads AI ecosystem strategy and commercial growth by developing enterprise data licensing opportunities, channel partnerships, and relationships with AI companies and platforms. Owns opportunity development from proposals through contract execution, presents real-world data solutions, and collaborates across product, analytics, marketing, pricing, solutions, and legal teams. Establishes team goals and drives pipeline generation, forecasting, proposal quality, and operational excellence.

Own the technical roadmap, backlog, architecture direction, and delivery execution for Takeda’s AI-native large molecule discovery software products. Partner with business, scientific, engineering, data, and ML leaders to translate discovery workflows into scalable technical requirements and releases. Manage Agile delivery, technical risks, integrations, KPIs, external development partners, and architectural alignment across scientific platforms. Apply biology and laboratory workflow expertise to guide AI-enabled product development and technical trade-offs.

Leads the technical product strategy, backlog, architecture, and delivery roadmap for Takeda’s AI-native laboratory endpoint generation products. Translates scientific and business needs into technical requirements, coordinates engineering, data science, ML, and infrastructure teams, and ensures integration with laboratory platforms such as ELN/LIMS and scientific data lakes. Owns technical trade-offs, delivery quality, engineering KPIs, external partners, and alignment across the Labs of Tomorrow portfolio while enabling AI/ML-driven scientific workflow redesign.

Leads AI/ML application to large-molecule drug discovery, including antibody, bispecific, ADC, and other biologics design. Develops generative, predictive, and optimization models; manages large biological datasets; integrates computational methods with automated Design-Predict-Make-Confirm experiments; and partners with cross-functional drug development teams. Provides strategic direction, mentors scientists, identifies portfolio opportunities, and communicates technical insights to senior stakeholders.

Leads solution architecture for the Manheim Marketplace, designing scalable systems, modernizing technology, guiding engineering and product teams, and integrating AI capabilities. Responsibilities include architecture reviews, standards development, non-functional requirements, AI use-case identification, agent orchestration strategies, proofs of concept, governance coordination, mentoring, and technical documentation.

Sell Abnormal AI cybersecurity solutions to enterprise organizations with more than 3,000 mailboxes. Responsibilities include prospecting, pipeline generation, complex deal management, contract negotiation, closing new logos, account expansion, renewals, accurate sales-system documentation, ROI development, and cross-functional collaboration with sales engineering, marketing, product, and customer success teams.

Leads the LEGO Group’s global demand planning capability across regions, channels, and planning horizons. Owns the demand planning vision, operating model, governance, standards, performance measures, and transformation roadmap. Aligns Commercial, Operations, Supply Chain, Finance, Technology, and regional stakeholders around planning outcomes. Builds organizational capability, strengthens forecasting performance, establishes global consistency, and leads adoption of technology-enabled planning practices.

Leads complex technical programs for an enterprise client, coordinating engineering, operations, and sales stakeholders. Responsibilities include defining outcomes, building delivery plans, managing risks and dependencies, establishing governance, driving change, and communicating performance. The role also requires applying AI agents to program orchestration, scaling program-management practices, and providing technical guidance on software development and platform architectures.

Lead full-cycle recruiting for Harvey Labs’ specialized AI research organization. Partner with technical leadership to define recruiting strategies, map talent markets, source exceptional researchers and engineers, manage searches through negotiation and close, and provide market intelligence on talent availability and compensation. Build scalable recruiting processes while advising leaders, operating through ambiguity, and using modern AI tools to improve sourcing, research, outreach, and recruiting operations.

Lead full-cycle recruiting for Harvey Labs’ specialized AI research organization. Partner with technical leadership to define talent strategies, map candidates across industry and academia, source exceptional researchers and engineers, manage searches through negotiation and closing, and provide market intelligence on talent availability and compensation. Build scalable recruiting processes, advise leaders on hiring profiles, and elevate technical recruiting across the company.

Three-month summer internship supporting Cadence EDA applications for silicon, package, and system design. Interns receive training in design, verification, synthesis, timing analysis, physical implementation, analog layout, signoff analysis, embedded software, hardware/software co-design, scripting, and AI-enabled design flows. The role involves collaborating with application engineers and technical experts while developing communication, analytical, presentation, and engineering problem-solving skills.

Analyze complex aerospace and defense datasets to develop predictive analytics, optimization algorithms, machine learning solutions, scripts, dashboards, and automated processes. Collaborate with data engineers, modelers, web developers, and customers to understand problems, interpret data, and deliver actionable insights supporting military leadership and mission solutions.

Conduct fundamental and applied research in embodied AI, agentic AI, robotics, robotic foundation models, world models, simulations, perception, control, manipulation, and interaction. Develop and evaluate AI/ML models, collaborate across interdisciplinary teams, publish findings, communicate research outcomes, and support proposals and partnerships. The position is fully onsite at Brookhaven National Laboratory and requires a recently awarded Ph.D. in computer science, computer engineering, electrical engineering, or a related field.

Develop and maintain custom applications, APIs, integrations, reports, automation, and AI-enabled solutions for business functions including Finance, HR, Payroll, and Legal. Gather requirements, improve workflows, troubleshoot systems, support deployments, document solutions, and implement security and data governance controls. Collaborate with technical and non-technical stakeholders, vendors, and third-party providers while delivering solutions in a Microsoft .NET environment.

Own the architecture, roadmap, governance, evaluation, and operations of TraceLink’s OPUS Brain, the cognitive foundation for governed AI agents. Lead applied AI, ML, and agent-systems engineers developing reasoning, planning, memory, orchestration, decisioning, and learning capabilities. Establish responsible AI, observability, simulation, guardrails, auditability, and human-in-the-loop controls. Partner with product, engineering, security, compliance, legal, and customers to deploy reliable LLM-based agentic systems across regulated supply chain operations.

Leads Ingram Micro’s global AI partner enablement program, developing curriculum, certification paths, readiness assessments, and learning journeys. Manages global cohorts, vendor-funded initiatives, cross-functional teams, governance, reporting, and partner adoption. The role drives AI capability, certification, monetization, and measurable revenue outcomes across countries and business units while collaborating with engineering teams, hyperscalers, and technology partners.

Leads strategic adoption of AI for cybersecurity, including identifying use cases, evaluating AI technologies, developing roadmaps, managing cross-functional projects, and ensuring security, privacy, and compliance. The role bridges AI, security operations, threat intelligence, incident response, and executive stakeholders while overseeing pilots, implementation plans, metrics, training, and change management.

Develop and implement AI governance strategies, policies, approval processes, and control frameworks supporting responsible AI adoption. Assess AI risks, security, privacy, ethical, and regulatory considerations; manage governance artifacts, vendors, data sources, and proofs of concept. Educate stakeholders, lead cross-functional initiatives, influence senior leaders, and partner with Security, Legal, IT, Product, business teams, and external vendors.

Drive prospecting, consultative solution selling, and closing for Twilio’s new products across enterprise accounts. Build strategic customer relationships, validate sales motions and use cases, manage complex multi-product deals, develop territory strategies, and collaborate with product, finance, legal, marketing, and engineering teams. Maintain accurate Salesforce pipeline and forecasts while serving as a customer advocate and technical subject matter expert.

Build and own production AI systems, including knowledge pipelines, tool-using agents, automated evaluations, and secure enterprise workflows. Develop backend services, measure AI quality, prevent security risks, and deliver solutions from design through production. Collaborate with product, customer-facing, and engineering teams to solve complex business problems using real-world enterprise data.