AI and machine learning hub building agentic and RAG products for S&P Global
Kensho is the AI innovation arm of S&P Global, building machine learning and retrieval products on a Python-centric stack of FastAPI, Django, PyTorch, Hugging Face Transformers and LangGraph. Job posts cluster around agentic platforms, RAG pipelines and vector search, showing a shift from classic ML (LightGBM, XGBoost, scikit-learn) toward LLM orchestration. Hiring is accelerating and engineering-heavy, with a smaller product and sales layer.
Kensho Technologies develops AI and machine learning products as part of S&P Global, supporting its data, benchmarks and ratings businesses. Founded in 2013, the company is headquartered in Cambridge, Massachusetts, with an additional office in New York City. It employs between 51 and 200 people, and engineers make up the large majority of the team. Its specialties span machine learning, data science and cloud computing, running on AWS with EKS, Kafka, PostgreSQL and OpenSearch. Current hiring is concentrated in the United States.
Kensho uses Python, TypeScript, FastAPI, Django, PostgreSQL, Kafka, Redis, OpenSearch, AWS EKS, PyTorch, Hugging Face Transformers, LangGraph and observability tools like Prometheus, Grafana and Sentry.
Job posts point to agentic applications, a mature agentic platform, end-to-end RAG pipelines, large-scale retrieval systems and open-source tool contributions.
Yes. Hiring is accelerating and dominated by engineering, spanning mid, senior and intern levels, with smaller product and sales openings, all in the United States.
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Kensho Technologies's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.