AI Platform Engineer, Agentic AI & Distributed Systems

AI Platform Engineer Agentic AI & Distributed Systems Role Overview We are looking for a highly skilled Platform Engineer to build and scale enterprise-grade AI technology focused on Agentic AI systems, Large Language Models (LLMs), distributed orchestration, and cloud-native infrastructure. The ideal candidate will have strong expertise in AI engineering, backend systems, Kubernetes-based deployments, and modern programming frameworks to help design, develop, and operate scalable AI-native platforms and autonomous agent ecosystems. Key Responsibilities * Design, develop, and optimize Agentic AI systems, multi-agent orchestration frameworks, and AI workflow platforms. * Build and maintain scalable infrastructure for LLM training, fine-tuning, inference, and evaluation pipelines. * Develop backend services, APIs, orchestration layers, and automation frameworks using Python and TypeScript. * Engineer cloud-native distributed systems using Kubernetes, Docker, and modern DevOps practices. * Implement CI/CD pipelines, observability, infrastructure automation, and platform reliability tooling. * Work with vector databases, knowledge graphs, retrieval systems, and AI memory architectures. * Optimize GPU workloads, model serving infrastructure, and inference performance. * Build secure, production-grade AI deployment pipelines across development, staging, and production environments. * Collaborate with product, research, and engineering teams to deliver enterprise AI solutions. * Contribute to platform architecture, scalability, resilience, and operational excellence initiatives. Required Skills & Experience * Strong hands-on experience with Agentic AI frameworks and AI orchestration systems. * Experience building applications using LLMs, AI agents, RAG architectures, and autonomous workflows. * Strong understanding of language model training, fine-tuning, evaluation, and inference optimization. * Proficiency in Python programming for AI/ML and backend engineering. * Proficiency in TypeScript programming for APIs, orchestration services, and platform tooling. * Strong experience with Kubernetes, Docker, distributed systems, and cloud-native infrastructure. * Experience with DevOps engineering, CI/CD pipelines, Infrastructure as Code, and automation tooling. * Experience with AI infrastructure including GPUs, model serving, vector databases, and scalable inference systems. * Familiarity with cloud platforms such as Azure, AWS, or GCP. * Strong understanding of API architecture, microservices, and event-driven systems. * Experience with monitoring, logging, observability, and platform reliability engineering. Preferred Qualifications * Experience with frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar agentic frameworks. * Familiarity with distributed training frameworks and model optimization techniques. * Experience with Apache Kafka, Temporal, Redis, PostgreSQL, or graph/vector databases. * Knowledge of enterprise AI governance, security, and compliance architectures. * Exposure to MLOps and AI platform engineering best practices. * Experience building enterprise-scale AI products or developer platforms. What We’re Looking For * Strong problem-solving and systems thinking abilities. * Ability to work across AI, infrastructure, and product engineering domains. * Ownership mindset with strong execution capability. * Passion for building scalable AI-native systems and next-generation developer platforms. * Ability to thrive in a fast-paced startup and innovation-driven environment.