Top Artificial Intelligence Jobs

Leads hands-on design, development, deployment, and support of enterprise agentic AI applications. Designs multi-agent workflows, RAG pipelines, vector search, MCP integrations, and LLM solutions. Provides technical leadership, code reviews, mentorship, and architectural guidance while establishing engineering standards for CI/CD, testing, security, scalability, and responsible AI. Partners with executives and stakeholders to translate AI strategy into delivery plans and evaluates emerging AI technologies.

Own audience selection, purchasing, delivery, and new product development for an identity-data and AI platform. Define requirements, validate opportunities with customers, manage releases, measure outcomes, and discontinue underperforming initiatives. Partner with sales, marketing, engineering, and data teams across consumer and business marketing. Analyze match rates, coverage, record counts, and source economics using SQL, while applying AI tools and designing machine-consumable products.

Leads external communications strategy for product launches and strategic partnerships. Develops messaging, press strategies, internal alignment, partner PR materials, executive talking points, and media programs. Collaborates with Product Marketing, Product, alliances, content, social, PR agencies, and partner communications teams. Manages journalist relationships, tracks media coverage and engagement, and uses performance insights to improve campaigns.

Conduct technical research and data-driven assessments of emerging C-UAS technologies, systems, and operational capabilities. Use Maven Smart System, Palantir, Power BI, Python, and AI tools to evaluate performance, interoperability, maturity, and mission relevance. Develop dashboards, reports, roadmaps, capability gap analyses, briefings, and acquisition recommendations while supporting experimentation, requirements development, market research, and technology transition. Collaborate with engineering, acquisition, intelligence, operational, and military stakeholders in support of C-UAS capability development.

Lead malware analysis, reverse engineering, digital forensics, incident response, threat intelligence, and cyber threat assessments supporting USCYBERCOM. Analyze compromised systems, media, logs, malware, adversary TTPs, and intelligence data; develop indicators and signatures; produce technical reports and leadership briefings; support incident response policies, operational planning, risk assessments, and cyber situational awareness. The role requires collaboration across cyber and intelligence organizations and an active Top Secret clearance with SCI eligibility and polygraph.

Leads Arctic Wolf’s global marketing technology ecosystem and campaign operations engine. Oversees Marketo, Salesforce integrations, data governance, AI adoption, vendor management, campaign execution, attribution, budgeting, MDF administration, and operational standards across email, webinars, direct mail, and content syndication. Manages a distributed global team and partners with marketing, sales operations, revenue operations, finance, IT, and business applications to deliver scalable, compliant, high-quality campaigns aligned with growth and pipeline objectives.

Leads strategy, roadmaps, backlogs, adoption, and continuous improvement for collaboration and AI-enabled technology products. Partners with business stakeholders, architecture, engineering, vendors, and technology teams to deliver measurable productivity and user outcomes. Owns product lifecycle activities, prioritization, stakeholder communication, adoption metrics, risk management, and product health. Evaluates emerging technologies, including Microsoft collaboration platforms and AI, to guide product decisions and enterprise technology investments.

Develop and deliver secure, AI-enabled, cloud-native full-stack solutions for lending platforms. Build APIs, integrations, reporting capabilities, and applications using Azure, .NET, Python, React, SQL, and ETL technologies. Apply Prompt Engineering, MCP, and RAG patterns; implement CI/CD pipelines; support observability, governance, security, and compliance. Collaborate with architects, business partners, QA, and engineers, participate in reviews, guide junior developers, and maintain technical documentation.

Lead ASAPP’s product strategy, portfolio, and product organization as it scales enterprise AI products. Define product direction, convert AI research into reliable commercial offerings, identify repeatable customer needs, and oversee products from incubation through adoption and expansion. Partner closely with customers, engineering, research, sales, delivery, and design while setting standards for AI quality, safety, reliability, metrics, and operational execution. Recruit and develop exceptional product and design leaders and guide enterprise positioning, packaging, and deployment strategy.

Leads AI and technology value-creation engagements across portfolio companies. Assesses business operations, workflows, systems, data, and economics; identifies and prioritizes technology opportunities; develops ROI-focused business cases; advises executives on AI adoption; and transitions validated initiatives to product and engineering teams for implementation and measurement.

Directs national physician and allied health credentialing operations across U.S. and Philippines teams. Oversees staff, payor relationships, credentialing applications, delegated agreements, database systems, accreditation, revenue-cycle credentialing issues, denial resolution, claims support, and accounts receivable recommendations. Partners with managed care, legal, compliance, regulatory, and onboarding teams to ensure providers are credentialed and able to bill by their start dates.

Leads strategy, roadmaps, backlogs, adoption, and continuous improvement for collaboration and AI-enabled technology products. Acts as product owner, partnering with business stakeholders, architecture, engineering, vendors, and technology teams. Defines product vision, priorities, success metrics, and delivery plans while balancing user needs, business outcomes, technical constraints, security, risk, and enterprise standards. Uses user feedback, adoption data, and operational insights to guide enhancements and communicate product performance and recommendations.

Leads Hello Heart’s enterprise marketing strategy and team, driving B2B demand generation, qualified pipeline, positioning, messaging, sales enablement, partner marketing, events, and product launches. Partners with Sales, Customer Success, Partnerships, Product, and BDRs to support commercial growth across employers, consultants, health plans, and strategic partners. Owns campaign performance measurement, KPIs, experimentation, and optimization while embedding AI into marketing strategy and operations.

Build and operate production AI-powered developer tools, including code review assistants, test generators, deployment diagnostics, and incident-response agents. Develop the self-service platform supporting deployment pipelines, observability, security, cost management, and reliable AI systems. Integrate LLM providers, agent frameworks, MCP servers, CI/CD, and infrastructure platforms. Own features from design through production, participate in on-call, improve operational practices, collaborate cross-functionally, and mentor engineers.

Set technical direction for AI-powered developer tools and a self-service AI platform. Design, build, and operate production AI agents, scalable distributed systems, deployment frameworks, observability integrations, security controls, and CI/CD integrations. Establish LLM and agent-development standards, lead cross-team initiatives, mentor engineers, conduct design reviews, measure AI-tool effectiveness, and participate in on-call operations.

Contribute to AI-enabled workflows for transmission and distribution operations. Study utility procedures, develop operator decision-support use cases, create workflow models, evaluate operational effectiveness, and identify opportunities to improve grid reliability and operator efficiency. Collaborate with engineers, product managers, and AI specialists, and present recommendations to technical leaders. The role requires power systems knowledge, Python, data analytics, machine learning, and generative AI familiarity.

Build and maintain AI applications and agents from prototype through deployment. Translate client business problems into technical solutions, connect applications to Power BI, Microsoft Fabric, and business systems, troubleshoot reliability and performance issues, and validate AI responses. Lead client discussions, demonstrations, training, milestone tracking, and scope management while creating reusable templates and documentation. Use agentic coding tools, evaluate emerging AI technologies, and collaborate with consultants and clients.

Tenure-track Assistant Professor will conduct cognitive psychology research, teach undergraduate and graduate courses, mentor students, pursue external funding, and collaborate across cognitive science, AI, education, engineering, and health. Preferred research areas include generative AI, large language models, human-AI interaction, learning and memory, educational technology, cognitive modeling, and computational approaches to behavior. The role also includes university service and contributions to interdisciplinary research and public engagement.

Lead a new product line from discovery through launch, owning its vision, strategy, roadmap, requirements, metrics, and performance. Partner with engineering, conduct customer and market research, create data-driven insights, and manage post-sale relationships with key biopharma accounts. Develop AI-assisted workflow tools and collaborate on account strategy, renewals, and expansion opportunities.

Teach Upper School technology and computer science courses, including programming, AP Computer Science, CAD/CAM, cybersecurity, fabrication, and artificial intelligence. Develop engaging project-based instruction, assess student learning, integrate technology across the curriculum, and collaborate with the Educational Technology Department. Communicate with students and families, advise students, participate in school committees and events, pursue professional development, and maintain a safe, inclusive classroom environment.

Leads logistics business insights by applying advanced analytics, AI, machine learning, automation, and reporting to improve service, cost, capacity, productivity, and sustainability. Builds data foundations, governance, stewardship, and enterprise reporting solutions; deploys digital tools; identifies automation opportunities; tracks KPI value; and coaches logistics teams in data-driven decision-making. Partners with operations, IT, and vendors to embed scalable analytics and digital transformation into logistics workflows.

Leads enterprise LLMOps, AgentOps, and MLOps capabilities, including AI deployment, monitoring, governance, evaluation, reliability, FinOps, and continuous improvement. Owns the AI operations roadmap, standards, service model, and adoption strategy while partnering with security, risk, infrastructure, architecture, and business teams. Builds a multidisciplinary team, manages strategic vendors and budgets, establishes responsible AI controls, and reports on adoption, operational health, cost efficiency, and risk.

Leads enterprise AI initiatives from use-case identification through production scaling. Partners with business, technology, risk, legal, and compliance teams to prioritize AI opportunities, manage governance, define KPIs, track business value, drive adoption, and ensure responsible, secure, compliant implementation. Provides executive reporting and coordinates cross-functional delivery across concurrent AI programs.

Leads a span of approximately 20 engineers while shaping hiring, onboarding, career development, staffing, and engineering enablement across the AI practice. The role is also approximately 50% billable client delivery, providing executive advisory on AI software development lifecycles, governance, agentic deployments, MLOps and LLMOps pipelines, cloud platforms, observability, and production resilience. Requires extensive engineering leadership, organizational scaling, consulting, GCP, and production AI/ML deployment experience.

Build and lead a scalable platform engineering function spanning CI/CD, infrastructure, observability, developer tooling, environments, and production operations. Develop internal tools, reusable automation, paved roads, and AI-assisted workflows that improve developer experience, delivery reliability, and engineering productivity. Partner across teams, guide architecture and standards, measure DORA and DX metrics, and shape the platform roadmap while providing hands-on technical leadership.