Senior AI Infrastructure Engineer

About Us
At Plurai, we believe the future is agentic, set to transform industries in ways we can’t yet imagine. But today’s GenAI is fragile. Reliability gaps, performance failures, and lack of safeguards are slowing adoption and stalling innovation. We’re here to change that. We’re building the foundational infrastructure to make GenAI systems reliable, resilient, and production-ready, and assembling a world-class AI engineering and research team to push the boundaries of what GenAI can achieve.

The Role
We are hiring a Senior AI Infrastructure Engineer to join our founding core team. You will play a pivotal role in designing, implementing, and owning the infrastructure that powers large-scale data processing, LLM-driven workflows, and agentic systems. This is a hands-on position for someone who thrives in ambiguity, enjoys deep technical ownership, and wants to shape both architecture and engineering culture from the ground up.

Responsibilities

• Build backend services and internal platforms and cloud-native tooling
• Design scalable infrastructure for data orchestration, API integrations, and real-time systems
• Set up and maintain CI/CD pipelines, observability, and developer environments
• Work closely with the founding team on architecture decisions, roadmap prioritization, and experimentation
• Interface with GenAI frameworks, vector DBs, and emerging agent tooling

Requirements

• 5+ years of engineering experience in backend, infrastructure, or data platforms
• Proven track record of building systems from scratch in fast-moving, high-ownership environments, ideally at early-stage startups
• Strong coding skills and experience with cloud platforms (AWS/GCP)
• Deep understanding of databases, pipelines, and pipelines architectures, microservices, and orchestration tools
• Excited by intelligent systems, GenAI tooling, and system-level challenges

Bonus Points

• Hands-on experience with GenAI frameworks: LangChain, LlamaIndex, etc.
• Proficiency with infrastructure-as-code: Terraform,
• Container orchestration experience: Kubernetes, Docker
• Familiarity with orchestration engines: Argo, Dagster
• Experience with vector DBs (e.g., Pinecone, Qdrant) or agent frameworks (e.g., AutoGen, LangGraph)