AI Solutions Engineer

Business Area: Sales Engineering Seniority Level: Mid-Senior level Job 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. We are looking for a highly technical, customer-facing AI Solutions Engineer to act as the tip of the spear for our enterprise go-to-market motion. This is not a "slideware" or pure presentation role. You will embed with prospective clients, rolling up your sleeves to architect, build, and deploy end-to-end Data, ML, and Generative AI proofs-of-concept (PoCs) and Minimum Viable Products (MVPs). You will leverage the best paradigms of the modern data stack—combining the streaming and hybrid-security prowess of the Cloudera ecosystem with the unified Lakehouse and AI/ML developer experience ecosystem. Your ultimate goal is to prove technical value through working code, turning complex business problems into production-ready AI applications that secure the technical win. As an AI Solutions Engineer, you will: Prototyping: Lead hands-on technical engagements. Build custom, production-grade AI/ML prototypes, RAG (Retrieval-Augmented Generation) pipelines, and data ingestion workflows directly in the customer's environment to prove business value. Pre-Sales Technical Leadership: Act as the primary technical advisor during the sales cycle. Lead deep-dive architectural whiteboarding sessions, handle technical objections, and translate ambiguous business needs into concrete, scalable data architectures. Lakehouse Architecture Design: Architect modern, open data lakehouses. Design pipelines that stream data via Apache NiFi or Flink into open table formats (Apache Iceberg or Delta Lake), optimizing for both BI and AI workloads. AI/ML Orchestration: Utilize frameworks like MLflow and Cloudera Machine Learning (CML) to manage the end-to-end ML lifecycle. Train, fine-tune, and deploy predictive models and open-source LLMs (e.g., Llama 3, Mixtral) against enterprise data safely and securely. Cross-Functional Collaboration: Act as the feedback loop between the customer and our internal Product/Engineering teams, advocating for feature requests and identifying gaps in the current product suite based on real-world deployment challenges. We are excited about you if you have : Technical Expertise You should be deeply comfortable operating across the modern data and AI continuum: The "Cloudera" Stack (Data in Motion & Hybrid): Deep understanding of high-throughput data ingestion and stream processing (Apache NiFi, Apache Flink, Apache Kafka). Experience with hybrid-cloud deployments, granular Role-Based Access Control (RBAC), and Apache Iceberg. Lakehouse & ML Ops: Strong proficiency in distributed compute (Apache Spark). Hands-on experience with Delta Lake, MLflow for model registry and tracking, and unified workspace environments for collaborative data science. Generative AI & LLMOps: Proven ability to build GenAI applications. Experience with orchestration frameworks (LangChain, LlamaIndex), Vector Databases (Milvus, Pinecone), and prompt engineering. Development & Infrastructure: Expert-level Python and advanced SQL. Comfortable with containerization (Docker, Kubernetes) and deploying applications via REST APIs (FastAPI/Flask) or lightweight frontends (Streamlit/Gradio). Experience: 5+ years in a highly technical, client-facing role (e.g., Solutions Engineering, Forward Deployed Engineering, Technical Consulting) or as a Senior Data/ML Engineer who frequently interacted with business stakeholders. Builder's Mentality: A GitHub repository, portfolio, or track record demonstrating your ability to independently build and ship full-stack data/AI applications from scratch. Communication: Exceptional ability to explain complex, distributed systems and advanced AI concepts to both C-level executives and deeply technical engineering teams. Agility: Comfort operating in a fast-paced, ambiguous pre-sales environment where requirements change rapidly and time-to-value is the primary metric. 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-ZY1