Top Artificial Intelligence Jobs

Conduct quantitative research on market behavior and trading strategies. Responsibilities include discovering predictive patterns, designing statistical and machine-learning models, building AI research agents, developing large-scale research infrastructure, running experiments and backtests, and translating findings into production-ready trading signals. Interns complete an end-to-end research project while collaborating with researchers and technologists.

Supports employee lifecycle administration, personnel records, HR inquiries, recruiting coordination, onboarding, background checks, I-9 processing, orientations, HR programs, reporting, audits, and internal HR resources. The role also coordinates training and HR initiatives, maintains SharePoint and intranet content, and supports process improvements and technology implementation.

Leads broadcast and digital sales operations, develops revenue strategies, drives new business, manages forecasting and receivables, and cultivates client relationships. Oversees hiring, training, performance evaluation, and development of sales personnel while serving as a digital sales thought leader. Requires at least five years of digital or media sales experience, strong communication and leadership skills, Microsoft Office proficiency, knowledge of AI and digital reporting metrics, and a valid driver’s license.

Lead and scale the US BDR team, owning pipeline generation, coaching, recruiting, forecasting, and performance management. Build an AI-native outbound engine using autonomous sequencing, signal-based prospecting, intent monitoring, and conversation intelligence. Partner with Marketing, Sales, RevOps, Product Marketing, and Strategy to refine ICPs, improve lead routing and handoffs, instrument funnel performance, and create scalable playbooks for a multi-market BDR organization.

Lead and expand a strategic enterprise account within the financial services sector. Build C-suite relationships, develop joint business plans, structure and negotiate complex multi-million-dollar SaaS deals, collaborate with internal teams on tailored solutions, advocate for client needs, and achieve sales and profitability targets. The role requires deep financial services knowledge, consultative enterprise sales expertise, strategic leadership, and travel of up to 50%.

Own end-to-end delivery of core product features, build AI/ML pipelines for construction document and drawing analysis, and shape scalable frontend, backend, and ML architecture. Collaborate with co-founders and construction users, translate workflow needs into product improvements, establish engineering practices, and help grow the team. The role spans computer vision, LLM systems, frontend, backend, and production infrastructure in a fast-moving startup environment.

Design and ship production LLM features for a SaaS product: build customer intelligence from recordings and text, prioritize testimonials using metadata, create AI-powered surveys/interviews, iterate via research, prototyping, deployment, and evaluation. Own technical decisions and deliver measurable outcomes working closely with engineering leadership and customers.

Lead full-cycle sales for a digital marketing agency expanding beyond automotive and collision repair. Responsibilities include outbound prospecting, discovery, proposal development, closing high-value retainers, entering new verticals, maintaining HubSpot pipeline accuracy, collaborating with creative and performance teams, and using AI tools to improve prospecting and outreach.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Design, develop, and deploy AI-native software products using multi-agent workflows, large language models, geospatial data pipelines, and cloud infrastructure. Build autonomous agents with tool use, structured reasoning, feedback loops, and reinforcement mechanisms. Develop scalable data ingestion systems, integrate secure enterprise environments, and operate production AI systems using DevOps practices. Contribute to engineering standards and leverage AI-assisted development tools for software design, testing, and documentation.

Leads the design and delivery of secure, scalable distributed systems and AI-enabled applications. Responsibilities include architectural leadership, Java or Scala development, cloud engineering, CI/CD, infrastructure automation, API integration, retrieval-augmented generation, agentic workflows, responsible AI adoption, mentoring, and establishing engineering quality and security standards.

Perform contract drafting, review, redlining, and simulated negotiations while evaluating AI-generated legal responses. Identify contractual risks, assess legal accuracy using structured rubrics, and provide actionable feedback to improve AI systems for contract review. Collaborate with legal, product, engineering, and research teams on datasets, evaluation guidelines, and quality standards.

Full-stack software engineering intern partnering with senior engineers to build and maintain applications across front-end, back-end, APIs, databases, and cloud infrastructure. Responsibilities include feature development, system design, automated testing, code reviews, CI/CD, infrastructure as code, production monitoring, incident response, and cross-functional collaboration. The role also involves using and critically reviewing AI-generated code and integrating AI tools into software development.

Full-stack Software Development Engineer Intern building end-to-end features across front-end, back-end, APIs, databases, cloud infrastructure, and AI-integrated components. Responsibilities include system design, coding, testing, code review, CI/CD, infrastructure as code, production monitoring, incident response, and collaboration with product managers, designers, and engineers. Interns will use AI coding assistants and LLM APIs while evaluating generated code for correctness, security, performance, and maintainability.

Lead AI product strategy and strategic operations across a product portfolio. Responsibilities include market assessments, market sizing, buy/build/partner analysis, quarterly reviews, annual planning, budgeting, hiring, KPI tracking, executive stakeholder management, and AI initiatives that drive growth and operational efficiency. The role partners with Product, Engineering, Finance, and senior leadership in a fast-paced enterprise SaaS environment.

Leads the design, experimentation, productionization, and optimization of machine learning, deep learning, generative AI, LLM, and agentic systems. Develops Python-based proofs of concept and production solutions, evaluates and tunes models, integrates generative AI into ML platforms, improves system performance, and partners with product and engineering teams. Acts as an ML subject matter expert while mentoring practitioners and influencing product and technical decisions.

Leads Mastercard’s enterprise AI and data strategy, responsible AI governance, research, and horizon scanning. Develops frameworks, guardrails, assessment models, and best practices for generative AI, agentic AI, machine learning, and advanced analytics. Partners with legal, privacy, compliance, risk, technology, product, and business teams to manage emerging risks and regulatory expectations. Advises senior leaders, promotes AI literacy, embeds responsible practices into workflows, and mentors colleagues across the organization.

Leads Mastercard’s enterprise AI and data strategy, including responsible AI frameworks, governance, risk assessment, regulatory monitoring, and integration of generative and agentic AI. Partners with legal, privacy, compliance, risk, technology, product, and business teams to establish guardrails, translate emerging developments into strategic guidance, improve AI literacy, and mentor practitioners.

Lead BlackLine's enterprise AI transformation: define strategy, governance, and measurable outcomes; build and run AI program and team; partner with business and IT to design, deploy, and adopt AI agents and automation; enforce responsible AI, data governance, and compliance; report progress to CIO and senior leadership.

Own the full sales cycle for Qualitate’s growth equity and venture capital segment, from prospecting through contract close. Build pipeline, run tailored demos, manage complex multi-stakeholder evaluations, convert pilots, expand strategic accounts, and provide product feedback. The role also contributes to sales playbooks, pricing, packaging, compliance workflows, and competitive positioning in an early-stage environment.

Own the full sales cycle for Qualitate’s AI-powered primary intelligence platform in the public equity market. Responsibilities include prospecting funds, leveraging industry networks, running tailored demos, managing trials and proof-of-concepts, navigating multi-stakeholder buying processes, closing contracts, and shaping the emerging sales playbook, messaging, competitive positioning, and CRM standards.

Leads architecture and hands-on delivery of production-grade software, machine learning, generative AI, RAG, and AI-agent solutions. Builds cloud-native services, APIs, data integrations, MLOps/LLMOps pipelines, evaluation frameworks, and secure deployment patterns. Owns technical initiatives from experimentation through production, including reliability, observability, testing, incident resolution, responsible AI, and cost optimization. Influences cross-team architecture and roadmaps while mentoring engineers without direct management responsibilities.

Build and operate the backend for Bilt’s AI-powered Concierge across chat, SMS, email, and iMessage. Responsibilities include agent tools and workflows, multi-agent orchestration, model routing, distributed systems, messaging, authentication, performance optimization, evaluation harnesses, and proactive engagement features. The role requires production backend experience, LLM familiarity, cloud service operation, strong distributed-systems fundamentals, product judgment, AI coding-agent usage, and clear technical writing.

Drives strategic business development for automation and intelligence solutions serving municipalities and consulting engineers in the water and wastewater sector. Responsibilities include identifying and closing complex opportunities, providing technical consultation, developing proposals, negotiating contracts, managing stakeholder relationships, building partnerships, tracking sales KPIs, and representing the company at industry events. The role requires expertise in automation, SCADA, instrumentation, AI analytics, water infrastructure, and complex long-cycle sales.

Leads Cisco Networking’s AI/ML product strategy, vision, roadmap, and scalable data platform development. Directs and mentors product managers while partnering with engineering, design, go-to-market, and Cisco’s central AI team. Engages enterprise customers, identifies AI-driven solutions to networking and digital experience challenges, and guides development of native AI/ML capabilities across networking products.