Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
Yesterday
ETLMachine LearningAzureDatabricksGenerative AIKubernetesPostgreSQLPythonStakeholder ManagementVault
Job Description
Job Title: Solutions AI Architect
Location: Remote
Duration: 12 months Contract
Location: Remote
Duration: 12 months Contract
Remote conditions: CST/EST preferred. Candidates open to limited travel at times.
Position Overview
- We are seeking an experienced AI Architect to lead the design and delivery of AI-enabled capabilities across a portfolio of enterprise digital products. This is a highly hands-on architecture role that combines AI/ML prototyping, solution architecture, technical governance, and cross-functional leadership.
- The ideal candidate will have strong experience developing AI/ML solutions in Python and Azure Databricks, architecting solutions across multiple products, and deploying applications within Azure Commercial environments, particularly using Azure Databricks, PostgreSQL, and Azure Kubernetes Service (AKS).
- This role is approximately 50% hands-on AI/ML development and prototyping, making practical implementation experience as important as architecture expertise.
Key Responsibilities
AI/ML Solution Development
- Design, prototype, and validate AI/ML capabilities using Python and Azure Databricks.
- Develop and evaluate Generative AI solutions using the OpenAI API, as well as traditional machine learning, forecasting, optimization, and predictive modeling approaches.
- Translate business and operational requirements into scalable AI/ML prototypes and production-ready solution designs.
- Evaluate model performance, technical feasibility, scalability, cost, and operational considerations.
- Transition successful prototypes and proof-of-concepts to engineering and implementation teams. Enterprise Solution Architecture
- Lead end-to-end architecture for AI-enabled capabilities from concept and prototype through implementation handoff.
- Design scalable, secure, maintainable solutions across a portfolio of interconnected digital products.
- Evaluate architecture tradeoffs involving cost, performance, security, data governance, scalability, and delivery timelines.
- Establish architectural patterns, technical standards, and reusable approaches across multiple product teams.
- Identify opportunities for shared services, reusable components, and technology standardization. Cross-Product Architecture & Governance
- Review solutions across multiple product teams to identify duplicated, conflicting, or inconsistent architectural approaches.
- Drive consistency across application, data, AI/ML, orchestration, planning, scheduling, and workflow capabilities.
- Establish and maintain architecture standards, design patterns, and technical guidelines.
- Participate in architecture and responsible-AI governance processes.
- Prepare architecture documentation, technical recommendations, decision records, and review materials.
- Address architecture review feedback and work with stakeholders to resolve technical issues. Technology Enablement
- Partner with engineering, data, cybersecurity, infrastructure, and product teams to translate AI and data opportunities into supportable enterprise capabilities.
- Provide technical guidance on Azure Databricks, PostgreSQL, AKS, AI/ML platforms, APIs, data architectures, and cloud-native technologies.
- Ensure proposed solutions align with enterprise security, data governance, infrastructure, and operational requirements.
- Support development teams through architecture decisions, technical challenges, and implementation handoffs. Leadership & Mentorship
- Mentor architects, software engineers, data engineers, and data scientists on AI, ML, data engineering, and solution architecture practices.
- Promote engineering best practices, reusable patterns, and effective AI/ML development methodologies.
- Communicate complex technical concepts clearly to both technical and business stakeholders.
- Influence technical direction across multiple teams and product areas.
Required Qualifications - Education & Experience
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field, or equivalent professional experience.
- 8+ years of progressive experience in IT, software engineering, digital products, AI/ML, or solution architecture; 10+ years preferred.
- Demonstrated experience in hands-on AI/ML development as well as enterprise solution architecture. Required Technical Skills
- Strong Python development experience for AI/ML prototyping and solution development.
- Must have strong hands-on experience with Azure Databricks, including AI/ML development and data processing.
- Experience developing forecasting, optimization, predictive analytics, or traditional machine learning models.
- Experience integrating Generative AI through the OpenAI API.
- Strong Azure Commercial experience in enterprise environments.
Hands-on experience with:
- Azure Databricks — Must Have
- Azure Kubernetes Service (AKS)
- PostgreSQL
- Azure DevOps
- Experience designing solutions for secure, controlled, or highly governed cloud environments.
- Comfortable working within GitHub Copilot-assisted development workflows. Preferred Qualifications
- Experience with Data Vault or Medallion architecture.
- Experience with modern ETL/ELT platforms and data integration tools, such as Fivetran.
- Experience with enterprise AI governance and responsible-AI review processes.
- Experience designing multi-product or portfolio-level architecture.
- Experience transitioning AI/ML proofs-of-concept into production implementations.
- Experience with AI orchestration, workflow automation, or enterprise GenAI platforms.
Core Competencies
- Enterprise and solution architecture
- Artificial intelligence and machine learning
- Generative AI
- Python development
- Azure Databricks
- Azure cloud architecture
- Kubernetes / AKS
- Data architecture and engineering
- Technical governance
- Architecture standards and design patterns
- Stakeholder management
- Technical leadership and mentoring
- Responsible AI and data governance
- Strong written and verbal communication
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