Are you passionate about working with cutting-edge technologies, tackling complex data integration challenges, and enabling seamless operations in multi-cloud environments? Join our team and play a pivotal role in shaping the future of Data ETL for Large Language Models (LLMs)!
We specialize in building ETL workflows for Retrieval-Augmented Generation (RAG) systems, empowering businesses to unlock the potential of unstructured data. With several trusted partners and an expanding vision, we are looking to add a new team member to grow our capabilities.
You will:
- Collaborate on integrating various databases, applications, and model providers, including AWS Bedrock.
- Build and maintain robust ETL pipelines for unstructured data across multi-cloud environments (Azure, AWS, and potentially GCP).
- Work closely with cross-functional teams to deliver scalable, secure, and efficient solutions.
- Contribute to infrastructure as code (IaC) practices using Pulumi and ArgoCD.
- Provide public-facing on-call support as needed, ensuring seamless operations and addressing customer concerns promptly.
Key Responsibilities
- Develop and deploy scalable solutions for integrating LLMs into RAG workflows.
- Enhance multi-cloud deployment capabilities to support Azure, AWS, and other platforms.
- Design and implement MLOps pipelines and automation for efficient model lifecycle management.
- Serve as a critical point of contact for public-facing on-call support, addressing technical issues effectively.
- Work in close collaboration with teams across UI, API layers, and infrastructure components.
What you’ll need to succeed in this role:
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Proven expertise in Kubernetes and Python: Demonstrated experience building and managing containerized applications.
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Strong MLOps background: Hands-on experience in developing and maintaining MLOps pipelines.
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Prior on-call experience: Ability to manage and resolve incidents in public-facing roles with professionalism.
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Excellent communication skills: Proficiency in written and spoken English to effectively interact with external and internal stakeholders.
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Multi-cloud experience: Familiarity with Azure and AWS is essential; GCP experience is a plus.
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Infrastructure as Code (IaC): Proficiency with tools like Pulumi and ArgoCD.