Senior AI/ML Engineer

Total Required Experience in Years: 15+ Years

Mode of Work: Remote / Hybrid Austin, Texas

Seeking an experienced Senior AI/ML Engineer to support a large-scale enterprise data modernization and migration initiative. The consultant will be responsible for designing, developing, deploying, and maintaining AI-driven automation and data reconciliation solutions that improve data quality, accelerate migration efforts, and reduce manual validation processes.

The ideal candidate will possess strong expertise in Azure AI/ML technologies, anomaly detection, machine learning pipelines, cloud-native data engineering, automated validation frameworks, and model monitoring within regulated government or financial environments.

Key Responsibilities

• Design and deploy AI/ML solutions for enterprise data migration and reconciliation programs.
• Build anomaly detection, exception classification, and root-cause analysis models.
• Develop AI-assisted data mapping and validation automation tools.
• Create automated reconciliation workflows eliminating manual validation activities.
• Design and maintain Azure Machine Learning pipelines and deployment frameworks.
• Develop cloud-native data ingestion and processing solutions.
• Build automated validation rules and exception management frameworks.
• Collaborate with business stakeholders to translate requirements into AI-driven solutions.
• Develop dashboards and reporting solutions for executive-level insights.
• Monitor model performance, accuracy, drift, and operational effectiveness.
• Implement MLflow tracking and model lifecycle management processes.
• Design data lineage, governance, and auditability frameworks.
• Support CI/CD automation for AI/ML and data engineering workloads.
• Mentor technical team members and provide knowledge transfer.
• Ensure compliance with governance, security, and regulatory requirements.
  
  

Required Skills

• Azure Machine Learning
• Azure Databricks
• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Delta Lake
• PyTorch
• Scikit-learn
• AI/ML Model Development
• Anomaly Detection
• Root Cause Analysis
• Exception Classification
• Data Reconciliation
• Machine Learning Pipelines
• MLOps
• MLflow
• Azure Monitor
• Model Drift Detection
• Azure Purview
• Azure Functions
• Azure Service Bus
• Docker
• Azure Kubernetes Service (AKS)
• Git-Based CI/CD
• Data Lineage Management
  
  

Secondary Skills

• T-SQL
• PL/SQL
• SQL Server
• Oracle Database
• Query Optimization
• Stored Procedures
• Partition Switching
• Columnstore Indexing
• Dashboard Development
• Agile Methodologies
• Requirements Analysis
• Technical Leadership
• Stakeholder Management
  
  

Required Qualifications

• 6+ years of AI/ML pipeline development and deployment experience.
• 6+ years of Azure data platform engineering experience.
• 10+ years of advanced SQL Server and Oracle database development experience.
• 6+ years of experience developing automated exception classification and validation frameworks.
• 4+ years of cloud-native data ingestion and microservices development experience.
• 4+ years of model monitoring, drift detection, and ML lifecycle management experience.
• Experience working within regulated government, financial, pension, or enterprise environments.
• Experience translating business controls and validation requirements into automated AI-driven workflows.
  
  

Preferred Qualifications

• Experience supporting pension modernization programs.
• Experience with large-scale enterprise data migration initiatives.
• Experience with regulated financial services environments.
• Experience building explainable AI and governance-focused AI solutions.
• Experience supporting executive reporting and operational analytics.
• Experience mentoring AI/ML engineering teams.
  
  

Deliverables

• AI/ML Models
• Anomaly Detection Frameworks
• Data Reconciliation Pipelines
• Exception Classification Engines
• Automated Validation Workflows
• Azure ML Pipelines
• Model Monitoring Dashboards
• Drift Detection Reports
• Data Lineage Documentation
• Technical Design Documents
• Executive Reporting Dashboards
• CI/CD Deployment Pipelines
• Knowledge Transfer Documentation
• Operational Runbooks
  
  

Education

• Bachelors Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Systems, or related field (or equivalent experience).