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Ragie

Lead Infrastructure Engineer

Ragie, San Francisco, California, United States, 94199

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This range is provided by Ragie. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range $200,000.00/yr - $250,000.00/yr

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Fractional Head of Technical Recruitment | Podcast Host | YouTuber @yournexttechstartup Ragie is a fully managed

RAG-as-a-service

platform that makes building RAG applications seamless for AI developers. We streamline ingestion, chunking, and multimodal indexing of structured and unstructured data, with built-in features like query rewriting, reranking, and flexible vector filtering to help enterprises deliver state-of-the-art GenAI. Ragie integrates directly into enterprise workflows, injecting accurate and actionable knowledge into mission-critical systems.

We are growing and we are looking for a

Senior Infrastructure Engineer

to join our core engineering team. This role is a unique opportunity to design and own the infrastructure behind a platform that runs multimodal GenAI workloads at scale. You’ll work with cutting-edge infrastructure technologies across

multi-cloud environments ,

GPU-accelerated compute , and

large-scale AI/LLM deployments .

Responsibilities

Architect, build, and maintain the foundational infrastructure for Ragie’s AI platform.

Design and manage

multi-cloud deployments

across providers such as Google Cloud, AWS, and Azure.

Deploy and scale

GPU clusters

for running LLMs and multimodal workloads efficiently.

Lead the setup and configuration of

Kubernetes clusters

for container orchestration and workload management.

Implement

Docker-based containerization strategies

to streamline application deployment and scaling.

Deploy and manage

Elasticsearch clusters

for large-scale indexing and retrieval.

Integrate and optimize

vector databases

(e.g., Pinecone, Weaviate, or equivalent) for hybrid search workloads.

Design and manage SQL and NoSQL databases, ensuring performance, reliability, and scalability.

Establish robust

observability practices

with monitoring, logging, and metrics solutions.

Partner closely with product and ML engineers to translate requirements into scalable, cost-efficient infrastructure.

Continuously optimize infrastructure for performance, resilience, and efficiency.

Requirements

6+ years of professional experience (preferably in startups or fast-paced environments), with at least 4 years in infrastructure engineering roles.

Hands-on experience building infrastructure from scratch using

Kubernetes, Docker, and Google Cloud Platform .

Proven experience managing

multi-cloud infrastructure

and orchestrating workloads across providers.

Strong expertise deploying and managing

GPU infrastructure

at scale.

Experience

running LLMs in production

and optimizing for latency, throughput, and cost.

Deep experience deploying and scaling

Elasticsearch clusters .

Familiarity with

vector databases

and search technologies.

Strong understanding of SQL and NoSQL databases.

Proficiency in scripting and automation (Python preferred).

Experience with observability tools such as Prometheus, Grafana, ELK stack, etc.

Ability to work autonomously and take initiative in a dynamic, evolving startup environment.

Excellent communication and collaboration skills across teams.

Competitive salary and equity options.

Opportunity to make a significant impact and shape the infrastructure of a rapidly growing startup.

Work with a world-class team building the next generation of RAG and multimodal GenAI.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Technology, Information and Internet

Referrals increase your chances of interviewing at Ragie by 2x

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