Senior AI/ML Engineer

Senior AI/ML Engineer:

Total Required Experience in Years: 15%2B 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%2B years of AI/ML pipeline development and deployment experience.

• 6%2B years of Azure data platform engineering experience.

• 10%2B years of advanced SQL Server and Oracle database development experience.

• 6%2B years of experience developing automated exception classification and validation frameworks.

• 4%2B years of cloud-native data ingestion and microservices development experience.

• 4%2B 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).