Data automation, reconciliation and regulatory reporting for financial firms
Gresham sells data control, reconciliation and regulatory reporting software to financial institutions, and its stack shows a heavy GenAI push: OpenAI, Gemini, Llama, LangChain, LangGraph, LlamaIndex, Pinecone and MCP sit alongside legacy Perl, IIS and .NET. Job posts call out adopting AI across legacy systems while building RAG search and multi-agent workflows. Hiring is accelerating, engineering-led and senior-weighted, spread across seven countries.
Gresham is a London-headquartered, privately held company founded in 1969, with 201–500 employees. It provides cloud and managed services for financial services firms covering enterprise data management, data automation, reconciliation and control, and regulatory reporting. Its focus areas include data quality, data governance, cash management, financial control and regulatory compliance. The company hires across India, the United States, Canada, the United Kingdom, Brazil, Australia and Singapore, with teams spanning engineering, data, sales, operations, support, finance, product and marketing.
Gresham uses Python, Java, .NET, Kotlin, Spring Boot, React and TypeScript, with Databricks, Apache Spark, Snowflake, Delta Lake and Apache Iceberg on AWS, plus Docker, Kubernetes, PostgreSQL and SQL Server.
Yes. Its stack includes OpenAI, Gemini, Llama, LangChain, LangGraph, LlamaIndex, Hugging Face, Pinecone and MCP, and job posts reference RAG, semantic search and multi-agent workflows.
Gresham is hiring in India, the United States, Canada, the United Kingdom, Brazil, Australia and Singapore, with engineering the largest hiring area and hiring velocity accelerating.
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Gresham'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.