Technical Lead Engineering · San Jose · Hybrid

Technical Lead

At Spectro Cloud, we turn innovation into real-world impact. Join us to build practical and scalable AI-powered solutions that matter.

We are seeking a talented individual to become an integral part of our Engineering team, shaping the future of our cutting‑edge Palette platform. As a software engineer, you will design, optimize, and streamline GoLang-based microservices and AI‑powered capabilities that form the foundation of our always‑on, self‑healing, declarative platform for managing infrastructure and applications. Proficiency in Kubernetes is required, as it lies at the heart of our cloud‑native, data center and edge solutions.

• Build production‑grade AI systems, designing, implementing, and maintaining LLM‑powered applications, agentic AI workflows, and RAG pipelines across multiple product use‑cases.
• Participate in guided technical labs covering prompt engineering, vector databases, LLM deployment tooling, multi‑agent orchestration, fine‑tuning strategies, and evaluation techniques.
• Develop, refine, and operationalize LLM solutions, including prompt design, retrieval strategies, embedding pipelines, Lang Chain/Lang Graph workflows, and API integrations using Python, Hugging Face, FastAPI, and similar frameworks.
• Ensure the seamless operation of our platform through automation, scripting, and rigorous testing, while maintaining high code quality.
• Stay ahead of emerging AI trends—small models, efficient inference (vLLM/Tensor
  
  RT), multimodal systems, on‑device LLMs—and recommend tools, frameworks, or integrations that enhance our platform.
• Collaborate closely with cross‑functional teams to create scalable, dependable, and secure solutions, continuously innovating to keep our solutions ahead of the curve.

• Embrace adaptability, tackle complex challenges, and navigate dynamic environments confidently.
• Break down intricate problems into manageable steps and deliver value through iterative, test‑and‑learn approaches.
• Champion innovation and collaboration, fostering a culture where shared ideas drive progress.

• 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 fundamentals in LLM/GenAI: solid understanding of large language models, prompt engineering, embeddings, vector search, RAG systems, and lightweight fine‑tuning (LoRA / PEFT preferred).
• Python expertise: proficiency and hands‑on experience with AI/ML libraries such as Hugging Face, PyTorch, Lang Chain, Lang Graph, FastAPI, or similar frameworks.
• LLM deployment experience: familiarity with Kubernetes‑based inference stacks including vLLM, llm‑d, Tensor
  
  RT, PyTorch Serve, or comparable deployment frameworks.
• Proficiency in at least one modern programming language such as Go, Java, or equivalent.
• Solid understanding of containerization and orchestration concepts, including Kubernetes.
• Deep understanding of microservices architecture and REST API design principles.
• Experience designing and building scalable, cloud‑native applications.
• Analytical problem‑solving: ability to debug model outputs, improve retrieval accuracy, optimize latency, and iterate quickly through experiments.
• Cloud & AI ecosystem knowledge: experience with AI/agent frameworks (Lang Chain, Auto Gen, Llama Index) and cloud platforms (AWS, Azure, GCP, etc.).
• Familiarity with virtual machine usage and integration within software solutions.
• Comfortable working in Linux‑based environments and using common command‑line tools.
• Experience with Cluster-API or deploying AI models to edge devices (NVIDIA Jetson, x86 edge nodes, ARM platforms) is a plus.
• Exposure to Kubernetes‑native developer tooling, observability, or MLOps pipelines is a plus.
• Kubernetes certification (CKA or CKAD) is a plus.