Top Artificial Intelligence Jobs

Own the full enterprise sales cycle for Oversee’s leisure travel business, from prospecting through closing. Build relationships with OTAs, agencies, tour operators, and vacation providers; develop pipeline; identify target segments and use cases; refine positioning and sales strategy; lead complex stakeholder processes; and partner with Product and Engineering to convert market insights into a repeatable leisure sales motion.

Build and operate developer-facing products for embodied AI, including APIs, UIs, packages, documentation, backend services, asset workflows, integrations, and asynchronous processing systems. Convert spatial reconstruction and mapping prototypes into production capabilities, support customer simulator and deployment integrations, diagnose reliability issues, and influence the product roadmap. The role requires full-stack product engineering, customer collaboration, and experience with 3D assets or comparable binary formats.

Drives enterprise AI adoption by understanding business workflows, configuring no-code and low-code agents, apps, and automations, analyzing feedback, developing onboarding materials, and supporting use-case requirements. The role translates business needs into AI solutions, defines KPIs and acceptance criteria, conducts demos, manages support channels, and partners with technical product managers on rollout, adoption, and continuous improvement.

Software development intern working with mentors and peers to design, implement, test, document, and review software features. The role involves learning development tools and programming practices, completing simple coding tasks, participating in design discussions and code reviews, incorporating feedback, and building domain knowledge. Candidates need basic Java programming skills, strong analytical and communication abilities, attention to detail, teamwork, documentation, organization, and problem-solving skills. Current Computer Science or related degree students are eligible.

Leads integrated marketing programs showcasing AI’s impact through human-centered stories. Discovers and develops customer, community, and societal proof points; partners with Social, Community, Communications, Creative, and agencies; and manages briefs, production, budgets, launches, distribution, and measurement across channels. Builds scalable storytelling programs, local and national partnerships, and audience participation initiatives while ensuring credibility, quality, and thoughtful representation.

Supports R&D and Engineering operations through KPI reporting, data quality audits, process improvement, project coordination, and operational analytics. Identifies and implements practical AI and automation use cases, including AI agents and workflows, while improving reliability through testing, context management, human review, and governance. Partners with technical and business stakeholders to deliver measurable efficiency gains, document processes, support system integrations, and provide training and reporting to leadership.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Own and build production AI agents and automations across Finance, including FP&A, Accounting, Audit, Tax, and Treasury. Lead the AI roadmap, quantify business outcomes, establish governance and SOX controls, integrate systems such as Oracle ERP and EPM, and manage a technical finance team. Partner with executives, technology, data, and audit stakeholders to scale secure, auditable automation that improves margin, productivity, and enterprise value.

Own technical relationships with strategic enterprise customers throughout Moveworks implementations. Design AI agent solutions, enterprise integrations, workflows, and automations using APIs, iPaaS tools, cloud functions, and scripting. Advise customers on agentic AI roadmaps, coordinate cross-functional delivery, develop reusable capabilities, and mentor engineers. The role combines solution architecture, hands-on implementation, technical consulting, executive communication, and up to 25% travel.

Leads architecture strategy, roadmaps, governance, and solution design for a regulated enterprise’s digital experience portfolio. Partners with business, product, marketing, design, data, security, and engineering teams to deliver secure, scalable, reusable web and mobile experiences. Oversees modernization, cloud and SaaS adoption, integration patterns, technology risk, and Agile/DevOps delivery. Defines architectural approaches for AI-enabled channels, conversational experiences, personalization, automation, and reusable digital platform services.

Design end-to-end AI builder experiences that enable technical and non-technical customers to create, evaluate, and deploy AI agents and workflows. Conduct user research, simplify complex AI and business logic, prototype with AI-native tools, collaborate with product and engineering teams, and advocate for high-quality, intuitive product design.

Own reliability, automation, and observability across colocation facilities, on-premises GPU clusters, cloud environments, and customer-facing platforms. Provision and troubleshoot servers, networking, storage, Kubernetes, and hardware; build infrastructure-as-code and automation; manage capacity and cloud spend; create monitoring and alerting; support incident response, on-call operations, and root-cause analysis. Partner with hardware and software teams on CI/CD, QA, HPC workloads, and customer deployments.

Founding Creative Director responsible for the creative and communication strategy of websites, campaigns, brands, and incubated products. The role combines copywriting, interactive experience design, animation, real-time 3D, generative imagery and video, motion graphics, campaign creative, and hands-on creative direction. They will build reusable AI-first production workflows, oversee agency output, and ensure performance and accessibility standards while working directly with company leadership and clients.

Leads the design and hands-on development of production AI solutions, including multi-agent systems, self-improving evaluation loops, open-model integration, multimodal and voice pipelines, and full-stack applications. Engages strategic customers through discovery, workshops, prototypes, and production deployments. Sets technical direction, mentors solutions engineers, develops SambaStack tooling, publishes reference architectures, and communicates product feedback to engineering and product teams.

Develop and deploy production-grade AI and machine learning capabilities for national security and OPIR missions. Responsibilities include signal-processing automation, data processing, model development, evaluation, MLOps workflows, GPU optimization, streaming-data integration, and scalable deployment in operational environments. The role involves collaboration with engineers, mission subject-matter experts, and product teams, with emphasis on AI agents, NLP, LLMs, computer vision, microservices, and classified cloud environments.

Design, develop, and deploy production-grade AI/ML solutions for national security missions, including NLP, LLMs, generative AI, deep learning, and computer vision. Build scalable data pipelines, APIs, microservices, MLOps workflows, and cloud or edge-deployed systems. Optimize and evaluate models, integrate them into secure operational environments, and collaborate with engineering and mission teams. Document technical designs and support accreditation processes in classified settings.

Architect and build a cross-platform design product spanning mobile, desktop, web, cloud services, connected cutting machines, and hardware integrations. Lead AI-native engineering practices, LLM feature integration, architecture governance, secure and reliable connectivity, backend APIs, large-scale modernization, and safe releases. Partner across product, design, QA, firmware, manufacturing, and security while mentoring engineers and remaining approximately 90% hands-on.

Own the full provider growth funnel for Nearby AI, from acquisition through monetization. Build funnel metrics, run rapid experiments across outreach and onboarding channels, design automated lifecycle journeys, scale effective acquisition channels, and use AI and automation to improve conversion, retention, and costs. Partner with Product and Engineering to enhance onboarding and provider value, while expanding successful growth motions across verticals and geographies.

Engineering Manager, Applied AI leads and coaches engineers while remaining hands-on on client engagements. Responsibilities include reviewing architecture, agent, prompt, and evaluation designs; resolving technical and client challenges; managing staffing and delivery; hiring and onboarding engineers; and improving engineering practices. The role requires strong software engineering experience, Python expertise, client-facing delivery experience, and familiarity with agents, evaluations, multi-agent systems, and AI coding tools.

Designs and leads scalable enterprise AI and machine learning solutions for clients. Responsibilities include translating business challenges into AI strategies, architecting data pipelines and model-serving systems, selecting cloud platforms and frameworks, guiding implementation teams, establishing AI governance and security standards, optimizing system and model performance, operationalizing LLMs and generative AI, and mentoring engineers.

Leads strategic technical engagements for an AI inference platform from architecture evaluation through benchmarking, model enablement, deployment, and production rollout. Builds and manages a high-performing solutions engineering team, guides customer evaluations and deployments, translates customer requirements into product priorities, and develops scalable technical go-to-market assets. Requires deep expertise in AI inference, accelerator architecture, distributed systems, serving frameworks, performance optimization, and customer-facing technical leadership.

Serve as a technical partner to sales and customer success teams, advising high-value customers on cloud infrastructure and AI/ML solutions. Responsibilities include architecture reviews, proofs of concept, demos, onboarding, technical workshops, infrastructure optimization, LLM deployment and fine-tuning, GPU workload optimization, AI application design, data pipeline and database integration, escalations, documentation, and development of tools for premium customers. Collaborate globally with Engineering, Product, Support, and account teams.

Lead development of production-grade AI systems and intelligent agents for secure public-sector supply chain workflows. Design orchestration, planning, evaluation, observability, safety, and reliability capabilities for autonomous multi-step tasks. Establish technical strategy, architecture, and engineering practices while managing security, compliance, scale, availability, cost, and model behavior. Collaborate with product, engineering, customer-facing, and executive stakeholders, mentor engineers, and contribute to hiring and organizational growth.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Own the vision, roadmap, and delivery of AI use-case products, including LLM systems, agents, and evaluation pipelines. Translate customer and business needs into technical product requirements, make build or buy decisions, define AI quality and business metrics, and guide launches through governance and regulatory review. Lead cross-functional teams, manage executive stakeholders, establish AI product standards, mentor product managers, and ensure product quality, safety, adoption, and impact.