Engineering Manager, Enterprise AI Platform

About the position 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. At Cloudera, our Data Services Pillar is the heart of data innovation. We don’t just work with technology; we build it. Our mission is to empower data practitioners by creating seamless, enterprise-grade experiences for data engineering, warehousing, streaming, operational databases, and AI. Cloudera is looking for an Engineering Manager with a strong technical background to help manage the team(s) located in Santa Clara, California or in North America to help drive the development of Cloudera’s next-generation AI and machine learning platform. You will be responsible for managing a team that will 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. 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 an Engineering Manager you will…. As an Engineering Manager you would be responsible for working with Product Managers to define what capabilities should be built in the product. You will have to work with Product Managers to understand customer use cases and help them use our products effectively. You will be responsible for the growth of your reports. You should be able to fill in, to address gaps in process / practices followed by the team / organization. As a leader you should be able to lead by example. This role is not eligible for immigration sponsorship We are excited if you have…. This is your opportunity to build cloud-native solutions that are deployable anywhere whether in massive clusters on any cloud provider or in private data centers. You’ll work with cutting-edge technologies like Trino, Spark, Airflow, and advanced AI inferencing systems to shape the future of analytics. Your code will directly influence how data engineers, analysts, and developers worldwide find value in their data. We believe in the power of open source. You’ll collaborate with project committers, contributing upstream to keep technologies like Apache Hive and Impala evolving. You’ll harden these engines for rock-solid security, optimize them for peak performance, and make them effortlessly run across all environments. Join us and help build the trusted, cloud-native platform that powers insights for the most data-intensive companies on the planet.

Responsibilities

• working with Product Managers to define what capabilities should be built in the product
• work with Product Managers to understand customer use cases and help them use our products effectively
• responsible for the growth of your reports
• able to fill in, to address gaps in process / practices followed by the team / organization
• able to lead by example

Requirements

• 8+ years of experience in building enterprise software and 2+ years of management experience
• Experience building and deploying production generative AI applications leveraging open source foundation models, prompt engineering, fine-tuning, Retrieval-Augmented Generation (RAG), and/or Generative AI frameworks (LangChain, Guidance, etc.)
• Strong written and oral communication skills
• Good understanding of Engineering best practices
• Experience with containerization frameworks like Kubernetes, Docker
• Strong Understanding of Distributed Systems and building systems at scale
• Should be able to drive the architecture/design and provide technical direction & guidance to the team
• Self-driven and motivated, with a strong sense of ownership and craftsmanship

Nice-to-haves

• Experience with data science and machine learning tools (R, Python, Tensorflow, Spark, mlflow etc.)
• Experience with AI/ML orchestration software (Kubeflow, KServe, Knative)
• Experience with cloud technologies (AWS, GCE, Azure)
• Experience using Big Data technologies like Spark, Hive etc.

Benefits

• 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

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