Cloudera

1 month ago

Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Lead architecture and delivery of a cloud-native AI platform at Cloudera. Build enterprise AI services in Go/Node.js, deploy inference servers on Kubernetes, and create tooling to accelerate integration of foundation models. Own AI orchestration, RAG pipelines, security, and multi-tenant GPU scheduling, collaborating with UI/design and product teams to deliver a scalable, vendor-lock-free cloud experience across hybrid environments.

Location: San Jose

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•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.

Pay and Benefits

Perks:Paid LeaveRemote WorkLearning BudgetUnplugged Days

Key Requirements

•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.

Experience:6+ yearsAI/MLCloud computingEnterprise software

Education:Bachelor's

Skills:Problem-solvingCollaborationCommunicationLeadershipTeamwork

Languages:English

Tech Stack:PythonGoRustC++DockerKubernetesKServeKubeRayKnativeVLLMTritonONNXTorchServeLangChainLlamaIndexDocker/KubernetesGPT

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn

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Cloudera

1 month ago

Staff Software Engineer , Anywhere Cloud - AI Systems & Runtimes

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•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.

Pay and Benefits

Perks:Paid LeaveRemote WorkLearning BudgetUnplugged Days

Key Requirements

•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.

Experience:6+ yearsAI/MLCloud computingEnterprise software

Education:Bachelor's

Skills:Problem-solvingCollaborationCommunicationLeadershipTeamwork

Languages:English

Tech Stack:PythonGoRustC++DockerKubernetesKServeKubeRayKnativeVLLMTritonONNXTorchServeLangChainLlamaIndexDocker/KubernetesGPT

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn