Top Artificial Intelligence Jobs

Develop and deploy foundational AI systems, including foundation model training, LLM inference, agent workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Build training and deployment pipelines, improve datasets and evaluation methods, support responsible AI practices, and mentor junior engineers while contributing to long-term technical strategy.

Design, develop, deploy, and support foundational AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize distributed AI systems for cost, latency, throughput, scalability, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor engineering teams.

Designs, develops, deploys, and supports scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. The role optimizes model performance, GPU/TPU utilization, latency, throughput, and cost; owns complex AI architecture; defines reliability objectives; leads technical reviews; and mentors engineering teams.

Conduct applied research in AI foundations, large language models, and agentic AI. Design, train, evaluate, validate, and deploy foundation models at scale using modern deep learning frameworks and cloud infrastructure. Develop novel methods, deliver platform or product code, collaborate with data scientists, engineers, and product managers, and communicate findings through technical reports or conference publications.

Design, develop, deploy, and support scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize model performance, cost, latency, throughput, and hardware utilization across production systems. Own complex AI architecture, reliability objectives, and technical roadmaps while ensuring security, compliance, and ethical alignment. Lead technical reviews, collaborate across engineering and product teams, and mentor senior and principal associates.

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture and cost-performance governance for scalable AI platforms, establish engineering standards, contribute to technical roadmaps, and mentor senior AI engineers. Collaborate with scientists, engineers, technical program managers, and product managers to deliver responsible AI products.

Conduct applied research in AI foundations, large language models, and agentic AI. Build and evaluate foundation models across training, validation, optimization, and deployment. Collaborate with data scientists, engineers, and product managers to deliver scalable AI products, translate research into business outcomes, and publish technical reports or conference papers. The role requires expertise in deep learning, model optimization, self-supervised learning, robustness, explainability, or RLHF.

Design, develop, deploy, and optimize large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and multi-model orchestration. Lead cost-performance governance, technical design reviews, AI engineering standards, and long-term platform strategy. Apply state-of-the-art optimization techniques to improve model scalability, latency, throughput, hardware utilization, and cost. Mentor senior technical leaders and collaborate with engineers, scientists, product managers, and program managers.

Design, develop, deploy, optimize, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Lead architecture, cost-performance governance, design reviews, and technical roadmaps for scalable production AI. Optimize model performance, hardware utilization, latency, throughput, and cost while ensuring responsible AI standards. Mentor senior technical staff and collaborate with engineers, researchers, program managers, and product managers.

Design, develop, deploy, optimize, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture and cost-performance optimization across scalable AI platforms, establish engineering standards, contribute to long-term technical roadmaps, and mentor senior AI engineers.

Supports evaluation, testing, rollout, measurement, and ongoing management of AI-enabled and legal technology solutions. Coordinates pilots, tracks product roadmaps and releases, monitors adoption, develops reports and dashboards, researches emerging capabilities, gathers user feedback, and maintains project documentation. Partners with technical and nontechnical stakeholders to assess product performance, identify adoption gaps, support training and communications, and inform rollout decisions.

Design, build, and deploy scalable AI/ML models and pipelines for consumer healthcare. Develop production code (Python/Java/Scala), automate infrastructure (Terraform, Kubernetes), validate model performance, integrate cloud services (Azure/AWS), and collaborate cross-functionally to monitor and document enterprise-scale AI solutions.

Build and deploy AI-powered products and internal tools by working directly with users to identify high-impact problems. Write production code, automate workflows, improve customer experiences, and own the full product cycle from discovery through deployment and adoption. Collaborate with sales, onboarding, and account management teams to drive measurable business outcomes. The role is highly autonomous, in-person, and involves regular client travel.

Develop scalable AI-powered operations and ML infrastructure for reliable, secure cloud systems. Design distributed systems, write maintainable code, improve architecture and operational excellence, mentor engineers, establish engineering standards, and lead testing, incident response, and on-call activities. The role requires Azure or cloud experience, coding proficiency, and expertise in automation, reliability, CI/CD, infrastructure as code, and responsible AI practices.

Leads product strategy and development for a mobile early-childhood education experience combining AI, digital caregiver tools, and analog activities. Owns the product lifecycle from concept through launch and ongoing iteration, using family insights to prioritize roadmaps and requirements. Collaborates closely with engineering, design, and marketing teams to build accessible, customer-focused consumer products in a fast-paced startup environment.

Drive growth in North American insurance markets by originating and closing complex technology services opportunities. Build C-suite relationships with insurance carriers, develop pipelines and account strategies, lead sales cycles, coordinate solution and delivery teams, and connect DXC capabilities to carrier priorities across policy administration, cloud, data, AI, modernization, and managed services. The role carries an expected annual sales target of approximately $10 million or more.

Apply machine learning, artificial intelligence, statistical analysis, and causal inference to large datasets and product analytics. Develop insights and recommendations for recommendation systems and user experiences. Evaluate experiments through planning, monitoring, and post-analysis, build data pipelines and tools, and communicate complex findings to stakeholders to support business decisions.

Own Sim’s marketing from positioning and technical storytelling through launches, distribution experiments, and performance measurement. Translate the AI platform’s technical capabilities into compelling messaging, content, demonstrations, and product narratives. Work directly with founders to reach builders and enterprise teams, drive activation and qualified pipeline, and use market feedback to shape go-to-market strategy and product direction.

Leads and develops a team of Business Development Representatives responsible for generating enterprise pipeline and meetings. The role includes hiring, coaching, performance management, career development, outbound sales strategy, forecasting, cross-functional collaboration, and optimizing sales processes with AI automation. The manager reports team performance to senior leadership and supports quota attainment across new and existing customer accounts.

Own AI-native startup accounts and manage the full sales cycle from outbound prospecting through production rollout. Generate pipeline, develop internal champions, lead technical evaluations, engage executive stakeholders, differentiate pricing and performance, and quarterback complex deals. The role requires infrastructure or API sales experience, technical fluency, procurement and security process knowledge, and close partnership with engineering, research, marketing, and deployment teams. Travel exceeds 50% monthly, with an in-office expectation in San Francisco or New York City.

Own AI-native startup accounts and drive revenue across the full sales cycle, from prospecting through production rollout. Generate outbound pipeline, develop internal champions, lead model evaluations, engage technical executives, and manage complex multi-threaded deals. Partner cross-functionally with Applied AI, Research, Engineering, Marketing, and Deployment to shape go-to-market strategy and customer experience. The role requires infrastructure or API sales expertise, technical fluency, and frequent travel.

Execute lifecycle marketing strategies for FanDuel Predicts across onboarding, activation, retention, monetization, and re-engagement. Build audiences, launch personalized campaigns, monitor performance, and optimize customer journeys using behavioral and transactional data. Develop experiments, analyze results, partner with Analytics, Product, Commercial, CRM Operations, and marketing technology teams, and translate insights into actions that improve engagement, retention, and customer lifetime value.

Leads Curri’s end-to-end data and AI strategy, including analytics, machine learning, data platforms, governance, and product intelligence. Owns the roadmap for routing, forecasting, pricing, and delivery optimization; moves models into production; partners with product and engineering; and builds a high-performing data and ML team. The role also oversees Snowflake-based data foundations, business metrics, decision support, and data quality and reliability.

Build and operate Citi’s scalable Generative AI common platform across on-premises and cloud environments. Responsibilities include designing reliable software, applying LLMs and RAG, partnering with development teams and business experts, maintaining security and SDLC compliance, and evolving the platform at scale. The role requires strong Python, distributed systems, architecture, Kubernetes, cloud, CI/CD, and MLOps expertise, along with leadership, project management, and communication skills.

Supports talent sourcing and recruiting pipeline management while analyzing recruiting funnels, building dashboards, optimizing candidate experiences, and researching compensation and market trends. The intern will work closely with executive leadership, manage ATS workflows, coordinate interviews, identify process bottlenecks, and recommend data-driven improvements. The role provides training for future product managers and requires strong analytical, communication, and process-building skills.