AI Solutions Architect - FS or CI Polygraph Required - Cloudera

Business Area:

Seniority 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.

As an AI Solutions Engineer within Cloudera ’s Public Sector Consulting team, you will be the technical architect and execution lead for agencies moving from "data chaos" to "agentic autonomy." You will work directly with government organizations to design, build, and deploy mission-critical AI applications on the Cloudera Data Platform (CDP).

This is not a "theoretical" role. You will be on the front lines of Phase 2 and Phase 3 adoption journeys—helping customers clean legacy data silos, select the right model architectures, and industrialize MLOps pipelines in highly secure, often air-gapped or hybrid-cloud environments.

As the AI Solutions Engineer you will:

1. AI Model Strategy, Selection and Implementation

Evaluate and select optimal model architectures (LLMs, SLMs, or traditional ML) based on mission requirements, considering tradeoffs between accuracy, latency, and cost.

Guide customers on "Build vs. Buy vs. Fine-tune" decisions, prioritizing open-source models (Llama, Mistral, Falcon) that can run securely within a sovereign data perimeter.

Experience building Agentic Workflows (AI agents that can execute API calls and multi-step tasks).

2. End-to-End Data Engineering

Design and implement robust data pipelines within CDP to transform "messy" legacy data into AI-ready formats.

Develop and optimize Vector Databases and Retrieval-Augmented Generation (RAG) architectures to ground AI responses in verified agency facts.

Build Data pipelines with Spark, Nifi, Kafka or other ETL tools.

3. Optimization & Performance Tuning

Optimize model inference for production environments using quantization, pruning, and hardware acceleration (NVIDIA GPU orchestration).

Implement LLMOps to monitor model performance, detect hallucination rates, and manage model versioning and drift.

4. Public Sector Advisory & Governance

Collaborate with the customer’s AI Center of Excellence (CoE) to establish automated guardrails for ethics, bias mitigation, and FedRAMP/IL5 compliance.

Translate complex technical AI concepts into mission-value briefings for GS-level stakeholders and agency leadership.

We’re excited about you if you have: (Minimum Qualifications):

Experience: 5+ years in Data Engineering, Machine Learning, or Software Engineering, with at least 2 years focused on Generative AI or Deep Learnin