[Remote] Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes
Note: The job is a remote job and is open to candidates in USA. Cloudera is a leading company in data management and cloud innovation, seeking a Staff Software Engineer to lead the architecture and delivery of their cloud-native AI platform. The role involves bridging AI research and production-grade Kubernetes environments while optimizing the management of open-source models and designing integration patterns for seamless AI capabilities.
Responsibilities
- Design and implement elegant, scalable application services (Go/Node.js) that wrap AI capabilities for enterprise use
- Lead the deployment of inference servers (vLLM, Triton) using KServe, KubeRay, or Knative to ensure serverless-style scaling for AI workloads
- Build internal tooling, SDKs, and 'AI Gateways' that enhance team agility and simplify the integration of Foundation Models (Llama, GPT) into product features
- Architect robust Retrieval-Augmented Generation (RAG) pipelines and prompt management services that integrate seamlessly with vector databases and enterprise data sources
- Partner with UI engineers, UX designers, and Product Management to ensure the AI platform is not just powerful, but highly usable for internal developers
- Ensure AI workloads are secure, multi-tenant, and optimized for GPU resource scheduling (MIG, fractional GPUs) within Kubernetes
Skills
- Bachelor's degree with 6+ years of software engineering experience (or equivalent Masters/PhD tenure), with at least 2+ years focused on AI/ML systems
- Expert proficiency in Python (for AI ecosystem) and strong competence in a systems language like Go or Rust/C++ (for high-performance serving layers)
- Deep understanding of LLM deployment challenges and runtimes (e.g., vLLM, ONNX, TorchServe, Triton). Familiarity with quantization techniques (AWQ, GPTQ) to optimize model size/speed
- Experience building complex workflows using tools like LangChain or LlamaIndex, and deploying them on containerized infrastructure (Docker/Kubernetes)
- Ability to navigate the rapidly changing AI landscape, filtering hype from practical engineering solutions, and driving technical alignment across teams
- Model Fine-Tuning: Experience with efficient fine-tuning techniques (PEFT, LoRA/QLoRA) on custom datasets
- GPU Optimization: Familiarity with CUDA programming or profiling GPU performance (Nsight systems)
- Open Source: Contributions to open-source AI projects (HuggingFace transformers, vLLM, etc.)
Benefits
- Generous PTO Policy
- Support work life balance with [Unplugged Days](https://www.youtube.com/watch?v=eXBMXiUHG8c)
- Flexible WFH Policy
- Mental & Physical Wellness programs
- Phone and Internet Reimbursement program
- Access to Continued Career Development
- Comprehensive Benefits and Competitive Packages
- [Paid Volunteer Time](https://www.youtube.com/watch?v=EHPK_ZRVRHA)
- Employee Resource Groups
Company Overview