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KT
Kforce Technology Staffing
Data and AI Architect
Career Insights for Generative Artificial Intelligence Engineer
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Based on Illinois data
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$123,205 / year median in Illinois
Job Description
RESPONSIBILITIES
Kforce has a client in Riverwoods, IL that is seeking an experienced Data & AI Architect to define and drive the data architecture strategy that powers enterprise AI, analytics, and machine learning initiatives. This role is responsible for designing scalable, AI-ready data ecosystems that support advanced analytics, generative AI, agentic AI, and intelligent automation solutions. The ideal candidate combines deep technical expertise in modern data platforms with a strong understanding of AI data requirements, governance, lineage, and enterprise architecture principles.Responsibilities:
- Define and maintain enterprise data architecture supporting AI, machine learning, and analytics initiatives
- Design scalable data models, pipelines, and integration patterns across cloud and enterprise platforms
- Establish standards for data ingestion, transformation, storage, governance, and consumption
- Architect solutions that unify structured and unstructured data into AI-ready datasets
- Develop and maintain data catalog, lineage, metadata, and data governance frameworks
- Partner with Data Engineering, AI/ML Engineering, Analytics, and Platform teams to ensure high-quality, reliable data foundations for AI initiatives
- Evaluate and recommend modern data technologies, integration tools, vector databases, and AI-focused data platforms
- Support enterprise data lake and modern data platform initiatives
- Create reference architectures, standards, data flow designs, and implementation guidance
- Drive architecture decisions that balance business value, scalability, security, performance, and cost
- Present architecture recommendations and technical strategies to both technical and executive stakeholders
- Stay current on emerging cloud data, AI infrastructure, and enterprise data architecture trends
REQUIREMENTS
- Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, or a related field (or equivalent experience)
- 8+ years of experience in Data Architecture, Data Engineering, Enterprise Data Management, or related disciplines
- 3+ years of experience designing and delivering data solutions supporting AI and machine learning workloads
- Deep expertise with cloud data platforms such as Snowflake, Google BigQuery, or equivalent technologies
- Experience designing and supporting enterprise data lake, data warehouse, or data mesh architectures
- Strong understanding of data modeling, ETL/ELT frameworks, data integration, and modern data architecture patterns
- Experience implementing data governance, metadata management, data cataloging, and lineage solutions
- Knowledge of AI/ML data requirements including feature engineering, vector embeddings, retrieval-augmented generation (RAG), and unstructured data processing
- Strong SQL skills and working knowledge of Python or similar scripting languages
- Excellent communication skills with the ability to translate technical concepts for business stakeholders
Preferred Qualifications:
- Relevant certifications such as SnowPro, Google Cloud Platform Professional Data Engineer, AWS Data Analytics, or equivalent
- Experience with advanced Snowflake capabilities, including Snowpark, Cortex, Data Sharing, and Dynamic Tables
- Experience with Google Cloud Platform services such as Vertex AI, Dataflow, Pub/Sub, and Cloud Storage
- Experience with vector databases, semantic search, knowledge graphs, ontologies, or AI-enabled knowledge architectures
- Familiarity with Model Context Protocol (MCP) or similar AI-to-data integration frameworks
- Experience supporting large-scale enterprise AI, analytics, or digital transformation initiatives The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role.