IT staffing and cloud, data, and AI engineering services firm
SIDRAM Technologies presents itself as an energy-efficiency platform provider, but its hiring tells a different story: a senior-heavy, engineering-dominated mix spanning AWS serverless, FPGA tooling (VHDL, Vivado, Quartus), and COBOL leadership points to a consulting and staffing model serving enterprise clients. Adoption of LangChain, LangGraph, RAG, and Copilot Studio alongside Azure migration work signals a pivot toward GenAI and cloud modernization engagements.
Notable leadership hires: Data Lead, COBOL LEAD, Azure Technical Lead, AI Lead
SIDRAM Technologies is a self-owned company founded in 2016 and headquartered in Cumming, Georgia, with 51–200 employees. It describes its original focus as platforms and tools that help utilities, retail energy providers, and consumers improve energy savings and drive sales through rebate programs. Its current hiring centers on engineering, data, and security roles across the United States and Canada. Technical work spans AWS cloud services, data pipelines on Spark, Glue, and Redshift, embedded and FPGA development, and enterprise AI implementation.
SIDRAM uses Python, FastAPI, Flask, AWS (Lambda, Fargate, DynamoDB, RDS, SageMaker, Bedrock), Terraform, GitLab, Apache Spark, AWS Glue, Redshift, plus FPGA tools like VHDL, Vivado, and Quartus.
Yes. Hiring is accelerating and weighted heavily toward senior engineering, with additional demand in data and security, plus leadership roles such as AI Lead, Data Lead, and Azure Technical Lead.
SIDRAM Technologies is headquartered in Cumming, Georgia, United States, and hires in the United States and Canada.
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SIDRAM 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.