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Data Engineer II

Job Description - Data Engineer II

Description

Our GenAI Platform team and help build enterprise-grade Generative AI capabilities and MCP (Model Context Protocol) tooling that power our semantic layer. This role is ideal for a Data engineer with a strong technical foundation who is excited about AI technologies, developer platforms, and building intelligent applications at scale.



Responsibilities

Reporting to a Senior Engineering Manager or Engineering Director, you will collaborate with engineers, architects, product managers, and data teams to develop scalable, secure, and reliable AI-enabled services that accelerate innovation across the organization.

  • Design, develop, and maintain services, APIs, and platform components supporting GenAI and semantic-layer capabilities.

  • Build and enhance MCP tools, adapters, and integrations that enable secure interaction between AI models and enterprise systems.

  • Implement and optimize retrieval-augmented generation (RAG), semantic search, embeddings, and knowledge retrieval solutions.

  • Partner with cross-functional teams to integrate AI capabilities into business applications and developer workflows.

  • Contribute to technical design discussions, architecture reviews, and engineering best practices.

  • Troubleshoot production issues, improve system reliability, and optimize performance and scalability.

  • Develop automated testing, monitoring, and observability solutions to ensure operational excellence.

  • Stay current on emerging trends in Generative AI, agentic systems, MCP, and semantic technologies.


Qualifications
  • Bachelor’s degree in computer science, Engineering, Information Technology, or a related field.

  • 2–5 years of software engineering experience developing scalable applications and services.

  • Proficiency in one or more programming languages such as Python, Java, TypeScript, or Go.

  • Experience building APIs, microservices, or developer tooling in cloud environments.

  • Strong understanding of software engineering principles, distributed systems, and system design fundamentals.

  • Experience with source control, CI/CD pipelines, automated testing, and agile development practices.

 

Preferred Qualifications

  • Hands-on experience with Large Language Models (LLMs), Generative AI applications, or AI development frameworks.

  • Familiarity with vector databases, embeddings, semantic search, and RAG architectures.

  • Exposure to MCP, agent frameworks, OpenAI tools, LangChain, LlamaIndex, or similar technologies.

  • Experience with AWS, Azure, or GCP cloud platforms.

  • Understanding of enterprise security, governance, and responsible AI practices



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