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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 take the best of the public cloud- cost efficiency, scalability, elasticity, and agility and extend it to wherever data lives: public clouds, private data centers, and even the edge. Powered by Kubernetes, our hybrid architecture separates compute and storage, giving customers maximum flexibility and optimized infrastructure usage. We are looking for a Staff Full Stack Software Engineer to lead the architecture and delivery of AI-powered workflows that are core to our product. You will define the technical strategy, set quality and reliability standards, and deliver end-to-end systems that transform ambiguous customer needs into robust, measurable, and privacy-safe AI experiences. You’ll partner closely with Product, Design, Data Science, and GTM to deliver high-impact features at scale.
Job Responsibility:
Own the architecture: Design, evolve, and document the end-to-end AI workflow stack
Ship production systems: Build reliable, low-latency services that integrate foundation models and traditional microservices
Own end-to-end delivery of features from the user-facing aspect (UI) to the backend services
Implement robust testing frameworks
Establish safety guardrails and human-in-the-loop processes
Optimize for cost & performance: Instrument, analyze, and optimize unit economics and performance
Drive data excellence: Shape data contracts, feedback loops, labeling strategies, and feature stores
Mentor and multiply: Provide technical leadership, unblock complex projects, raise code/design standards, mentor senior engineers
Partner across functions: Translate product intent into technical plans, influence roadmaps, communicate trade-offs
Requirements:
Bachelor’s degree in Computer Science or equivalent
6+ years of experience
Expertise in at least one primary language (Rust preferred) and ecosystem (e.g., Python, Go, or Java)
Expertise in cloud-native architectures (containers, service mesh, queues, eventing)
Proven experience in integrating AI/ML models into user interfaces
Familiarity with the AI/ML ecosystem (fundamentals of LLMs, vector databases, RAG, prompt engineering)
Familiarity with tools such as MLflow, LangChain, or Hugging Face
Security & privacy mindset (familiarity with data governance, PII handling, tenant isolation, compliance considerations)
Nice to have:
Platform thinking (experience designing reusable AI workflow primitives, SDKs, or internal platforms)
Model ops (experience with model lifecycle management, feature/embedding stores, prompt/version management, offline/online eval systems)
Search & data infra (experience with vector databases, retrieval strategies, indexing pipelines)
Observability (built robust tracing/metrics/logging for AI systems
familiarity with quality dashboards and prompt diff tooling)
Cost strategy (experience with model selection, distillation, caching layers, router policies, autoscaling)
Experience with managing machine learning workloads on container orchestration platforms like Kubernetes