Kensho Technologies
Kensho Technologies Offices
Kensho Technologies is headquartered in Cambridge and has 2 office locations.
Hybrid Workplace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
Not Specified
U.S. Office Locations
Cambridge
Kensho is located in the heart of Harvard Square within walking distance to shops, restaurants, bars and public transportation.
New York
55 Water Street, New York, NY, United States, 10038
Recently posted jobs
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
Own AI partnership development and a portfolio of strategic clients. Manage partner relationships, coordinate cross-functional launches, drive product adoption and expansion, convert trials, support renewals, and resolve partnership or client issues. The role requires technical fluency in AI/ML, APIs, and software implementation, along with strong communication, senior relationship management, commercial judgment, and comfort operating autonomously in ambiguous environments. Approximately 25% travel is required within the United States and to company hubs.
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
Own AI partnership development from qualification through launch while managing strategic customer accounts. Build partner relationships, coordinate cross-functional sales, product, engineering, legal, and marketing efforts, and drive commercial outcomes. Lead customer adoption, renewals, expansion, trial conversion, and time-to-value for API, enterprise, and developer products. Operate autonomously in ambiguous environments, create new playbooks, resolve engagement issues, and manage senior stakeholder relationships globally.
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
Design, build, and productionize agentic AI systems including LLM orchestration, retrieval, and evaluation. Work across the ML lifecycle from experimentation to deployment and monitoring, leverage proprietary structured and unstructured financial data, and collaborate with data, product, design, and MLOps teams to deliver scalable, robust agentic solutions.
