Technical Lead (AI/Kubernetes)

Location: San Jose, United States; hybrid. Applicants must be eligible to work lawfully in the U.S. immediately; visa sponsorship is not available.

Company

hirify.global develops Palette, an enterprise Kubernetes management platform for infrastructure and applications across data centers, cloud environments, and the edge.

What you will do

• Design, optimize, and maintain Go-based microservices for an always-on, self-healing, declarative platform.
• Build production-grade LLM applications, agentic AI workflows, and RAG pipelines across product use cases.
• Develop prompt designs, retrieval strategies, embedding pipelines, LangChain/LangGraph workflows, and API integrations.
• Deploy and operate AI models on Kubernetes using inference and orchestration tooling.
• Automate platform operations through scripting and rigorous testing while maintaining clean, efficient code.
• Evaluate emerging technologies such as efficient inference, small models, multimodal systems, and on-device LLMs.

Requirements

• Bachelor’s degree in Computer Science or a related technical field; 8+ years of software development experience, or 6+ years with a Master’s degree.
• Strong understanding of LLMs, prompt engineering, embeddings, vector search, RAG, and lightweight fine-tuning.
• Proficiency in Python and experience with Hugging Face, PyTorch, LangChain, LangGraph, FastAPI, or similar frameworks.
• Experience with Kubernetes-based LLM deployment, containerization, microservices, REST APIs, and scalable cloud-native applications.
• Proficiency in Go, Java, or an equivalent modern programming language, plus Linux and command-line tools.
• Strong analytical problem-solving skills, including debugging model outputs, improving retrieval accuracy, and optimizing latency.

Nice to have

• Experience with Cluster-API, edge AI deployments, Kubernetes-native developer tooling, observability, or MLOps pipelines.
• Experience with NVIDIA Jetson, x86 edge nodes, ARM platforms, or AI/agent frameworks such as AutoGen and LlamaIndex.
• CKA or CKAD certification.

Culture & Benefits

• Collaborative engineering environment focused on innovation and practical, scalable solutions.
• Iterative, test-and-learn approach to solving complex technical challenges.
• Cross-functional collaboration on secure and dependable AI-powered Kubernetes solutions.

Hiring process

• Initial screening interview.
• One or two technical interviews with hands-on coding assessments.
• Final round focused on team fit and detailed discussions; most interviews take place via Zoom.