AI/ML Oversight Engineer(20 Hrs/week)

AI/ML Oversight Engineer:

Duration:

2%2B Years (Part-Time 20 Hours/Week

AI/ML Oversight Engineer

Total Required Experience in Years: 15%2B Years

Mode of Work: Austin, Texas, Hybrid / Remote (Part-Time 20 Hours per Week)

Seeking an experienced AI/ML Oversight Engineer to support AI/ML validation, quality assurance, and governance activities within a large-scale enterprise data migration initiative. This role will serve as a hands-on technical specialist responsible for validating AI-generated outputs, reviewing pipeline architecture, verifying data integrity, monitoring system performance, and identifying operational risks across high-volume data processing environments.

The ideal candidate will possess strong software engineering experience, automated testing expertise, data validation knowledge, and the ability to communicate technical findings to both technical and non-technical stakeholders.

Key Responsibilities:

• Validate AI-generated outputs and automated decision-making processes.

• Review data pipelines to ensure integrity, accuracy, and compliance.

• Monitor system performance and identify operational risks.

• Analyze architecture, workflows, and delivery processes for quality assurance.

• Develop and execute regression testing frameworks.

• Build and maintain automated testing infrastructure.

• Validate high-volume data ingestion and processing workflows.

• Perform record count reconciliation and exception analysis.

• Verify data migration and bulk-load integrity.

• Review API integrations and asynchronous processing pipelines.

• Collaborate with engineering teams to improve system quality and scalability.

• Provide oversight on AI/ML delivery processes and governance standards.

• Create validation reports and communicate findings to stakeholders.

• Support quality reviews throughout development, testing, and deployment cycles.

• Document technical findings, recommendations, and remediation activities.

Required Skills:

• Python Development

• AI/ML Validation

• Software Engineering

• Async Pipeline Architecture

• REST API Development

• gRPC Services

• Regression Testing

• Automated Test Frameworks

• Test Automation

• Data Pipeline Validation

• Data Reconciliation

• Bulk Data Processing

• Record Count Verification

• Exception Identification

• Quality Assurance

• Performance Monitoring

• Risk Analysis

• Technical Documentation

Preferred Skills:

• AI Governance

• Machine Learning Operations (MLOps)

• Data Migration Validation

• Enterprise Data Platforms

• CI/CD Pipelines

• Cloud-Based Architectures

• Large-Scale Distributed Systems

• System Performance Analysis

• Audit and Compliance Support

Required Qualifications:

• 2%2B years of production software engineering experience.

• 2%2B years of Python backend development experience.

• 2%2B years of async pipeline architecture experience.

• 2%2B years of REST API and/or gRPC development experience.

• 2%2B years of experience building and maintaining scalable systems.

• 2%2B years of regression testing framework design and execution experience.

• 2%2B years of automated testing infrastructure development experience.

• 2%2B years of high-volume data pipeline validation experience.

• Experience with bulk-load verification, reconciliation, and exception management.

• 1%2B year of technical communication experience with cross-functional teams.

Preferred Qualifications:

• Experience supporting AI/ML initiatives.

• Experience validating enterprise data migration projects.

• Experience with governance-driven delivery environments.

• Experience supporting quality assurance activities for complex distributed systems.

• Experience working with regulated enterprise or government environments.

Deliverables:

• AI/ML Validation Reports

• Data Integrity Assessments

• Regression Test Plans

• Automated Test Frameworks

• Pipeline Validation Reports

• Risk and Issue Assessments

• Data Reconciliation Reports

• Exception Analysis Reports

• Quality Assurance Documentation

• Technical Review Findings

• Performance Monitoring Reports

• Knowledge Transfer Documentation

Education:

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

Email: [email protected]
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