Top Artificial Intelligence Jobs

Evaluate personalized AI responses by designing multi-turn prompts using your own personal context, assessing grounding, integration, and helpfulness, stack-ranking side-by-side model outputs, writing clear rationales, verifying debug info, and maintaining data hygiene. Work full-time as a remote contractor with schedule overlap requirements.

Hands-on internship building and programming opto-mechanical 3D machine vision and automated microscopy systems, automating data acquisition and image reconstruction, developing ETLs and databases, and deconstructing/analyzing advanced AI products. Collaborate with engineers on semiconductor, optics, and AI hardware projects and contribute technical research and tooling.

Lead design and implementation of Generative AI features and RAG solutions, integrate LLMs with internal systems, build APIs and workflows, mentor engineers, ensure enterprise SDLC, security, and responsible AI practices.

Design, build, and deploy production ML models (time series forecasting and NLP). Perform EDA, feature engineering, model evaluation, and translate business problems into ML solutions. Maintain production model-serving pipelines and collaborate across teams to deliver scalable data-driven systems.

Design, build, and operationalize enterprise-grade AI agents and an orchestration layer. Implement agent patterns, state management, observability, and governance. Integrate Azure/Azure AI services, support production-grade deployments, perform model/prompt updates, and provide technical leadership to scale reusable agent frameworks across the organization.

Evaluate personalized AI responses for Gemini by designing multi-turn prompts using personal data, comparing side-by-side responses, assessing grounding, integration, and helpfulness, writing structured rationales, extracting debug info, and maintaining data hygiene.

Lead enterprise Responsible AI and AI Governance by developing frameworks, policies, controls, and evaluation standards. Oversee reviews of AI use cases, track KPIs/KRMs, advise and challenge teams on risk and compliance, engage stakeholders and regulators, and drive continuous improvement and enterprise adoption of ethical, transparent, and compliant AI practices.

Lead design, development, and operationalization of enterprise Generative AI solutions (LLMs, RAG, agentic AI). Architect scalable cloud deployments, implement GenAIOps, observability, and secure CI/CD pipelines. Mentor engineers and partner with product, risk, and security teams to deliver production-ready, compliant AI systems.

Lead TrendAI's partner-facing product strategy for frontier AI providers and hyperscalers. Own joint roadmaps, define integration patterns, translate partner tech into product requirements, and drive co-innovation, deployments, and go-to-market with engineering, sales, alliances, and customers to deliver secure, reusable AI platform capabilities.

Build and maintain agentic toolkits that let LLMs take actions: design integrations for vendor APIs, write reliable tools, create tests and evals against real API behavior, tune tool descriptions and agent interactions, and contribute shared patterns to scale the catalog.

Senior Director Analyst delivers thought leadership and pragmatic research on AI-native and agentic software applications. Produce insights, presentations, and client advice; support sales and peer review; mentor junior analysts; research market trends, vendors, architectures, and production practices for AI/agent systems. Travel up to 25%.

Senior risk advisor partnering with Digital, Data, and AI leaders to identify, assess, and monitor strategic risks. Provide independent challenge on data governance, model and AI risk, third-party tech, cyber resilience, and operational scalability. Lead a team of risk practitioners, produce independent reporting, embed risk into strategic initiatives, and influence executive decision-making across the division.

Lead enterprise AI enablement and adoption programs, building self-service environments, learning academies, and embedded advocate networks. Drive change management, measure AI adoption as a business metric, ensure compliant AI use in regulated settings, and translate AI capabilities into usable solutions across research, clinical, commercial, and operations functions.

Lead AI-focused consulting workstreams: conduct research, build diagnostics, prototypes, and roadmaps; design AI strategy, operating models, data readiness, and responsible-AI governance; build/configure generative AI solutions; engage clients and coach junior staff to deliver high-quality, implementation-ready recommendations.

Lead strategy and commercial relationships for HealthVeritys AI ecosystem. Drive go-to-market planning, identify and close enterprise data licensing and channel partnerships, present solutions and lead technical due diligence, manage opportunities from proposal to contract, and coordinate cross-functional teams while establishing team goals and operational excellence.

Lead research and thought leadership in marketing measurement and AI-enabled decisioning. Produce actionable insights, client-facing advisory, presentations, and peer-reviewed content. Mentor analysts, support sales and GTM, improve research processes, and drive adoption of marketing analytics methods (MMM, experimentation, attribution, forecasting) and AI-powered measurement across clients and teams.

Define and govern enterprise AI architecture, standards, and reference implementations. Enable GenAI/ML platforms, integrations, and responsible AI guardrails. Partner with engineering, data science, cybersecurity, and business teams to translate use cases into scalable, secure production designs and drive adoption across the enterprise.

Lead design, deployment, and management of AIOps solutions using Splunk to provide predictive analytics and automated closed-loop incident response. Integrate telemetry from SolarWinds, ServiceNow, and other sources, build ML models with Splunk MLTK, ensure compliance with DoW security protocols, and coordinate with cyber defense teams.

Lead content strategy and AI-enabled content transformation for Consumer line of business. Define AI-driven content frameworks, partner across digital, SEO, analytics and product teams, modernize content planning/creation/measurement, and operationalize scalable playbooks to improve engagement and business outcomes while managing stakeholders and budgets in a matrixed, regulated environment.

Transform AI prototypes into secure, scalable production systems by re-architecting code, designing cloud infrastructure (AWS/Azure), implementing CI/CD, containerizing (Docker/Kubernetes), ensuring security/compliance, building APIs, monitoring, and enabling developer productivity with infrastructure-as-code, reusable templates, and documentation.

Work directly with customers to define AI strategy, identify high-impact use cases, and design, build, and ship production-grade AI agents and workflows. Rapidly deploy solutions in real environments, iterate with users and data, and contribute learnings back to the company's Mosaic product.

Lead program management for AI Transformation and Design Foundations, building roadmaps, governance, operating models, adoption plans, and metrics. Coordinate cross-functional teams (design, engineering, research, security, AI) to operationalize AI-assisted design practices, remove blockers, track risks and impact, and create playbooks and communication for scalable adoption.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Lead AI technical strategy and roadmap across product portfolio. Drive design, development, and production deployment of large-scale ML and generative AI models (including LLMs), mentor teams, align stakeholders, mitigate risks, and ensure timely delivery of AI capabilities.