Top Artificial Intelligence Jobs

Lead end-to-end recruiting for AI researchers, architects, and senior leaders across Redmond and Palo Alto. Responsibilities include market mapping, talent sourcing, offer strategy, executive advising, structured evaluation, candidate closing, and building scalable recruiting processes for a new talent acquisition function. The role focuses on highly competitive AI and research hiring markets, including candidates considering top-tier labs and major technology companies.

Own relationships with private equity and venture capital funds, converting them into partnerships, portfolio-company introductions, pipeline, and revenue. Build outbound and go-to-market motions, host events, influence sales opportunities, create partner materials, and develop scalable channel infrastructure. Collaborate cross-functionally with Sales, Marketing, Product, Customer Success, Solutions Consulting, and Accounting Partnerships. The role is hybrid near San Francisco or New York and requires significant travel.

Own product positioning, messaging, AI storytelling, go-to-market strategy, and launches for Trullion’s AI-powered accounting platform. Translate complex AI and automation capabilities into clear, trust-focused narratives, enable sales teams, maintain accurate website and content messaging, conduct competitive research, and gather buyer insights through customer interviews and win/loss analysis. Partner closely with product managers and cross-functional GTM teams while working onsite in New York City three days per week.

Process geospatial customer data through Python pipelines, validate and publish map layers, build automated quality checks, investigate AWS processing failures, and automate manual workflows. Collaborate with engineering and customer success to resolve field-reported issues and improve delivery processes.

Own and prioritize the product backlog, facilitate Agile ceremonies, write user stories and functional specifications, define acceptance criteria, and align engineering, design, and stakeholders. The Product Owner tracks delivery progress, oversees testing and validation, incorporates user feedback and performance metrics, and improves team workflows through clear documentation and proactive communication.

Drive enterprise sales by winning new logos, managing the full sales cycle, forecasting accurately, exceeding quota, planning accounts, selling to C-level stakeholders, and collaborating with sales engineering and development teams. The role requires consultative solution selling, ROI articulation, data-driven pipeline management, and use of sales methodologies such as MEDDIC. This is a hybrid position based in Boston, Massachusetts.

Produces and hosts events at Air HQ, managing planning, vendors, guests, budgets, logistics, and event communications. Maintains event and content calendars, coordinates photo and video capture, supports content operations, and transforms community programming into blog posts, social recaps, LinkedIn content, and case studies. Partners with internal teams, external media, culinary producers, and vendors to deliver creative experiences and strengthen Air’s presence in New York’s creative community.

Responsible for managing the full sales cycle, building relationships with enterprise clients, driving revenue, and collaborating across teams to meet sales targets.

Design and optimize the builder funnel to attract, onboard, engage, and retain developers and founders. Run programs (hackathons, cohorts), create onboarding resources, analyze KPIs to improve conversion and retention, and build partnerships to expand the ecosystem for decentralized AI and blockchain innovation.

Develop NLP and GenAI solutions for text classification, sentiment analysis, entity recognition, translation, and large-scale text analytics. Responsibilities include text preprocessing, feature engineering, model training and evaluation, exploratory data analysis, algorithm optimization, documentation, and collaboration with engineering and domain teams. The role requires applying machine learning, deep learning, statistical analysis, and distributed computing to extract insights from unstructured data.