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AI Solution Architect on an ongoing basis
to lead the design and delivery This role partners closely with development, infrastructure, and DevOps teams to ensure scalable, secure, and high-performing data systems. The AI Solutions Architect will collaborate with business stakeholders to translate requirements into modern AI/ML architectures and ensure successful implementation through all stages of the software development lifecycle.
Key Responsibilities
Architect and implement scalable AI and data engineering solutions across Data Warehouse and Data Lake environments
Partner with business stakeholders to understand requirements and translate them into robust technical architectures and delivery plans
Design and optimize ETL/ELT pipelines for data ingestion, transformation, and integration across multiple platforms
Build and operationalize AI/ML models in collaboration with data science teams, leveraging best practices in MLOps and automation
Collaborate with application developers, system administrators, and DevOps teams to ensure seamless deployment and monitoring of AI solutions
Champion performance tuning, scalability, and security in data and AI systems
Participate in Agile ceremonies and contribute to sprint planning, code reviews, and release management
Ensure adherence to enterprise architecture, security, and compliance standards
Required Qualifications
Bachelor's degree in Computer Science, Data Science, Engineering, or related field — or equivalent work experience
10+ years of proven experience in software development or data engineering roles
Expertise in
ETL/ELT development
and advanced
SQL programming
Proficiency in
data modeling ,
API integration , and
distributed data systems
Hands-on experience with one or more
cloud platforms
(GCP BigQuery, AWS Redshift, Azure Synapse)
Strong understanding of
AI/ML principles
and experience deploying or supporting
machine learning models
Familiarity with
Python
and popular AI frameworks (TensorFlow, PyTorch, scikit-learn)
Knowledge of
containerization
(Docker, Kubernetes) and
DevOps pipelines
for model deployment
Excellent problem-solving, analytical, and communication skills
Ability to collaborate effectively with both technical and non-technical teams in an Agile environment
Proven ability to manage multiple priorities and deliver high-quality solutions under deadlines
Preferred Qualifications
Experience designing and implementing
MLOps frameworks
Cloud certifications (AWS, Azure, or GCP preferred)
Familiarity with
data governance ,
metadata management , and
AI ethics/compliance
Compensation Competitive compensation and comprehensive benefits
Location Philadelphia, PA
Sprachkenntnisse
- English
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