AI, data engineering, and quality assurance for energy and utilities operations
JBS is a consulting and technology firm built around five service lines: AI/GenAI solutions (predictive models, LLM copilots, RAG), data engineering (cloud-native pipelines on Azure/AWS/GCP/Databricks), quality engineering (test automation, load testing), consulting (strategy and cloud modernization), and 24/7 ops/support (AIOps, MLOps, DataOps). The tech stack reflects a heavy Python + cloud (GCP, Azure, AWS, Databricks, Spark) footprint paired with modern DevOps tooling (Kubernetes, Terraform, Jenkins, GitLab CI/CD) and ML frameworks (LangGraph, AutoGen, scikit-learn, MLflow). Hiring is accelerating across engineering, data, and ops roles, with most placements at senior/director level—signaling a scaling consulting model that prioritizes senior technical capacity over junior headcount.
Notable leadership hires: Technical Director
JBS, founded in 2018 and headquartered in Frisco, Texas, serves Fortune 500 and high-growth companies in energy, utilities, and adjacent sectors. The firm operates through strategic partnerships with Microsoft Azure, Databricks, and Google Cloud. Their Energy & Utilities vertical covers solar, wind, CCGT, and multi-source operations, with solutions for renewable forecasting, grid intelligence, compliance automation, and Customer 360 platforms. Beyond energy, they work across generalist data strategy, governance, quality, modeling, and visualization engagements. The company operates in the 51–200 employee range.
GCP, Azure, AWS, Databricks, Apache Spark, Kubernetes, Terraform, Docker, Jenkins, GitLab CI/CD, Python, Java, C#, LangGraph, AutoGen, scikit-learn, MLflow, Snowflake, Salesforce, HubSpot, Jira, and Confluence.
Active projects include AI adoption roadmaps, reference architectures, and proof-of-concepts, with internal focus on expanding AI services in energy & utilities, driving consulting engagements, and scaling enterprise AI solutions.
Jade Business Services (JBS)'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.