Principal Forward Deployed Engineer – AI & Developer Platform

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Description

Accountabilities - Developer Experience and API Architecture Serve as the primary technical bridge between enterprise application developers, platform engineering teams, product managers, and senior technology leaders. - Design, validate, and standardize enterprise-grade REST, gRPC, and GraphQL APIs, Kubernetes Custom Resource Definitions (CRDs), and software development kits (SDKs). - Establish efficient developer workflows, continuous delivery pipelines, GitOps practices, and self-service developer portals using tools such as Argo CD and Flux. - Build command-line interfaces, testing frameworks, and automation tools that simplify adoption of Kubernetes and cloud infrastructure platforms. - Define and promote consistent API design principles, developer documentation standards, and software quality practices across engineering teams. - AI Engineering and Platform Architecture Architect production-ready infrastructure for real-time large language model inference, agent-based applications, and Retrieval-Augmented Generation (RAG) pipelines running on GPU-accelerated environments. - Standardize integration patterns for AI development frameworks and inference platforms, including LangChain, LlamaIndex, AutoGen, and vLLM. - Design scalable architectures for distributed AI workloads using technologies such as Ray, vLLM, SGLang, and Apache Spark. - Integrate vector databases, search systems, streaming technologies, and caching layers to support reliable and high-performance AI appli

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