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About This Role
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.
Cloudera is looking for a Staff Software Engineer to join the Enterprise AI Platform team and help drive development of Cloudera’s next\-generation AI and machine learning platform. You will be responsible for helping design, build, and deliver a platform that not only accelerates machine learning \& AI from exploration to production but also enables enterprises to create \& deploy Generative AI applications using foundation models with enterprise data at scale. This role requires an empathetic mindset and close collaboration with front\-end/web UI engineers, data scientists, designers, and product management.
We look for "The Startup Spark", a desire to create new things, dive in wherever there's a need, eagerness to make an impact as an individual, and the willingness to learn new things. You must be self\-motivated, innovative, and proactive. The role offers significant opportunities for growth.
Read about the Forrester Wave Report on Cloudera's Machine Learning offerings here.
As a Staff Software Engineer you will:
- Help build the leading platform for AI and Machine Learning in the enterprise.
- Design, code, and implement elegant, scalable, enterprise\-quality AI inference services powered by machine learning models.
- Design and Develop AI Model Registry and AI applications
- Work to enhance developer velocity and team agility.
- Build strong relationships and collaborate with platform and front\-end engineers, quality engineers, UX designers, as well as Product Management, Field, Professional Services, and other partners.
We are excited if you have (Required Experience):
- Bsc/Msc in related field or equivalent experience
- 10\+ years of experience building scalable microservices or applications using Go, Python, Node.js, C\# or Java
- Experience building and deploying AI Inference and Generative AI applications.
- Experience with foundation models, prompt engineering, fine\-tuning, semantic search and Retrieval\-Augmented Generation (RAG) using vector databases such as Pinecone, Milvus, etc.
- Experience with microservices design and development (Go, GRPC, SQL) on Kubernetes
- Demonstrate ability to go deep into technology and complex distributed systems
- Experience in crafting high\-level and low\-level design
- Experience in building highly scalable, robust and secure enterprise applications
- Self\-driven and motivated, with a strong sense of ownership and craftsmanship
- Strong written and verbal communication skills.
You may also have:
- Experience with HuggingFace, Nvidia AI frameworks and Nim models.
- Experience with AI/ML orchestration software KServe, Knative, Kubeflow.
- Experience with building AI applications with machine learning models using data science and machine learning tools (Python, Tensorflow, Spark, MLflow, R, etc.)
- Experience with at least one of the following Cloud technologies \- Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure
- Good to have some full\-stack experience with React, HTML, CSS.
- Experience with data science and machine learning tools (R, Python, Tensorflow, Spark)
- Deep understanding of cloud\-based networking
- Experience using Big Data technologies like Spark, Hive etc.
- Proven track record of collaborating with agile teams across geographically dispersed locations
This role is not eligible for immigration sponsorship or relocation.
*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
- Paid Volunteer Time
- Employee Resource Groups
EEO/VEVRAA
\#LI\-BV1
\#LI\-HYBRID
Salary Context
This $184K-$230K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 193 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,824 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Cloudera, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $234,620 based on 682 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($207K) sits 12% below the category median. Disclosed range: $184K to $230K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Cloudera AI Hiring
Cloudera has 1 open AI role right now. They're hiring across AI Software Engineer. Based in San Jose, CA, US. Compensation range: $230K - $230K.
Location Context
Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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