Role overview

Qualifications

Expert-level Python (Pandas, PySpark, SQLAlchemy)
Strong familiarity with C# for interacting with .NET-based data layers
Hands-on experience with Vector Databases and embedding models
Understanding of how data is exposed through Gravitee APIM and secured via MCP-specific authorization flows

Responsibilities

Design and optimize data schemas specifically for LLM consumption
Build robust data pipelines using Python and C#/.NET
Implement and maintain Vector Databases to support Retrieval-Augmented Generation
Work with the Gravitee API Gateway to enforce data masking and access control

Key facts

Remote from: Anywhere
Full time
Senior (5-10 years)
Data Engineer
English

Hard skills

Python (Programming Language) C# (Programming Language) Data Governance SQL (Programming Language) NoSQL Cloud Database Knowledge Graph Data Caching Contextual Design Build Pipeline Metadata Management

About the company

Everest Technologies, Inc

IT Services & IT Consulting

Founded in 1997, Everest Technologies is a leading Information Technology solutions provider based in Columbus, Ohio. We deliver top quality systems and software design, architecture, development, testing and implementation services to clients in a variety of industrial, commercial, and governmental environments. By focusing on achieving client successes, we have achieved success ourselves. Everest has grown steadily and is now recognized as a premier Information Technology solution provider in Ohio. Our reputation for providing creative and technically superior consulting services is built on our innovative use of leading technologies tailored to meet the individual needs of our clients. Additionally, our experienced consultants have augmented our clients’ internal staff to develop on-site and off-site technology solutions. The flexibility we provide, along with our focus on the specific needs of the project, allows us to deliver high-quality solutions to the client in a short amount of time. Everest Technologies provides its clients with top quality IT consultants dedicated to improving the clients’ business processes. The experience of our personnel assures successful implementation of IT solutions..

Company details

Company typeSME

IndustryIT Services & IT Consulting

Company size51 - 200

Links

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Job description

This is a remote position.

Senior Data Engineer - AI Context & Knowledge Systems

We are looking for a Data Engineer to build the "memory" and "knowledge" backbone of our Agentic AI ecosystem. You will be responsible for designing data pipelines that feed into our Model Context Protocol (MCP) servers, ensuring that AI agents managed via Gravitee have real-time access to accurate, secure, and contextually relevant enterprise data.

Key Responsibilities

Context Engineering: Design and optimize data schemas specifically for LLM consumption, ensuring that data retrieved via MCP servers is structured to minimize token usage and maximize reasoning accuracy.
Hybrid Pipeline Development: Build robust data pipelines using Python (for AI/ML workflows) and C#/.NET (for enterprise integration) to move data from legacy systems into AI-ready formats.
Vector Database Management: Implement and maintain Vector Databases (e.g., Pinecone, Weaviate, or Milvus) to support Retrieval-Augmented Generation (RAG) alongside live API tool calls.
Data Governance for AI: Work with the Gravitee API Gateway to enforce data masking, PII redaction, and fine-grained access control before data reaches an LLM.
Metadata Orchestration: Manage the OpenAPI and MCP metadata that allows AI agents to "understand" the data they are querying.

Technical Qualifications

Languages: Expert-level Python (Pandas, PySpark, SQLAlchemy) and strong familiarity with C# for interacting with .NET-based data layers.
AI Data Stack: Hands-on experience with Vector Databases and embedding models.
API Management: Understanding of how data is exposed through Gravitee APIM and secured via MCP-specific authorization flows.
Modern Data Stack: Experience with SQL/NoSQL databases, dbt, and cloud data warehouses (Snowflake, BigQuery, or Databricks).
Protocol Knowledge: Familiarity with the Model Context Protocol (MCP) and how it standardizes data retrieval for AI agents.

Preferred Skills

Experience building Knowledge Graphs to provide relational context to AI agents.
Familiarity with semantic caching to reduce LLM costs and improve response times.
Knowledge of Gravitee Observability for monitoring data drift in agentic conversations.