Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes
Cloudera is hiring a Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes in San Jose, United States. It pays $184k-$230k a year and Level rates it ; you can apply on Cloudera.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 10% above the typical software engineer posting on Level.
- The posting allows some remote work.
- Tools and skills the posting cites include Llama, LangChain and LlamaIndex.
- Level lists 56 other open roles at Cloudera.
AI in this role
Architect and deliver cloud-native AI platforms, orchestrating LLM inference servers and AI runtimes on Kubernetes.
Business Area:
EngineeringSeniority Level:
Mid-Senior levelJob Description:
At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.
Ready to take cloud innovation to the next level? Join Cloudera’s Anywhere Cloud team and help deliver a true “build your own pipeline, bring your own engine” experience — enabling data and AI workloads to run anywhere, without friction or vendor lock-in.
We bring the best of public cloud — cost efficiency, scalability, elasticity, and agility — to wherever data lives: public clouds, private data centers, and the edge. Powered by Kubernetes, our hybrid architecture separates compute and storage to maximize flexibility and optimize infrastructure usage.
This isn’t just cloud management — it’s about building a consistent, secure, and compliant cloud experience that gives organizations full access to all their data, anywhere.
With the acquisition of Taikun, we’re simplifying Kubernetes and cloud management even further, creating a unified, scalable, future-ready platform. If you’re passionate about Kubernetes — not just using it, but building it at the core, managing workloads across hybrid clouds and data centers, and obsessing over performance and DevOps — this is where you belong.
We are seeking a Staff Software Engineer to lead the architecture and delivery of our cloud‑native AI platform. In this high‑impact role, you will bridge the gap between cutting‑edge AI research and production‑grade Kubernetes environments. You will build the “nervous system” of our AI stack—optimizing how we run and manage open‑source models (Llama, Qwen, etc.) using K8s‑native patterns like Custom Resources (CRDs) and Operators, enabling agentic AI to thrive, and designing integration patterns that let our product teams and customers consume AI capabilities seamlessly.
As a Staff Software Engineer, you will:
Enterprise AI Services: Design and implement elegant, scalable application services (Go/Node.js) that wrap AI capabilities for enterprise use.
K8s-Native AI Orchestration: Lead the deployment of inference servers (vLLM, Triton) using KServe, KubeRay, or Knative to ensure serverless-style scaling for AI workloads.
Developer Velocity: Build internal tooling, SDKs, and "AI Gateways" that enhance team agility and simplify the integration of Foundation Models (Llama, GPT) into product features.
RAG & Prompt Engineering: Architect robust Retrieval-Augmented Generation (RAG) pipelines and prompt management services that integrate seamlessly with vector databases and enterprise data sources.
Cross-Functional Collaboration: Partner with UI engineers, UX designers, and Product Management to ensure the AI platform is not just powerful, but highly usable for internal developers.
Infrastructure & Security: Ensure AI workloads are secure, multi-tenant, and optimized for GPU resource scheduling (MIG, fractional GPUs) within Kubernetes.
We’re excited about you if you have:
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.
You May Also Have:
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.).
Why this role matters:
This is more than cloud management, it’s about building the foundation for a consistent, secure, and compliant cloud experience that gives organizations 100% access to 100% of their data, anywhere.
With the recent acquisition of Taikun, we are simplifying Kubernetes and cloud management even further, creating a platform that is unified, scalable, and future-ready.
If you are passionate about Kubernetes, not just using it but building it at the core managing workloads across hybrid clouds and datacenters and obsessed with performance, devops, etc. this is where you belong.
This role is not eligible for immigration sponsorship.
The anticipated annual base salary range for this position is:
California: $184,000- $230,000
Individual compensation within the published range is determined by the candidate's skills, experience, qualifications, and primary work location. In addition to base pay, sales roles are eligible for Cloudera's commission plan, while non-sales roles are eligible for the corporate incentive plan. All employees receive a comprehensive benefits package.
What you can expect from us:
Generous PTO Policy
Support work life balance with Unplugged Days
Flexible WFH Policy
Mental & Physical Wellness programs
Phone and Internet Reimbursement program
Access to Continued Career Development
Comprehensive Benefits and Competitive Packages
Employee Resource Groups
EEO/VEVRAA
#LI-SZ1
#LI-HYBRID
How we rate this
Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes at Cloudera rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $184k
- Typical software engineer job
- $167k
This posting starts 10% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where ai systems was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, AI Research, and AI Systems. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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