AI Solutions Architect

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