What are the responsibilities and job description for the AI/ML Engineering Lead position at Mansai Corporation?
About the Company
Company is a client operating in the public sector, supporting multiple state agencies through shared enterprise technology services. The organization focuses on delivering secure, scalable, and reliable AI/ML capabilities in a highly regulated government environment, with emphasis on responsible AI, cybersecurity, and privacy requirements aligned with standards such as FedRAMP and the NIST AI Risk Management Framework.
Key Responsibilities
Lead the architecture, development, implementation, and governance of a shared enterprise AI/ML platform supporting multiple state agencies
Deliver secure, scalable, reliable, and responsible AI/ML solutions across ML engineering, MLOps, cloud infrastructure, data engineering, and Generative AI
Build and operate shared enterprise AI/ML platforms supporting multiple teams or agencies
Establish MLOps practices including model registries, experiment tracking, automated testing, deployment, and monitoring
Design and manage data pipelines, feature stores, data quality, data lineage, and governance
Apply strong technical leadership in architecture, mentoring, security, and responsible AI
Ensure platform observability, reliability engineering, incident management, disaster recovery, and cloud cost optimization
Apply responsible AI practices including model explainability, fairness auditing, bias mitigation, and model risk management
Required Qualifications
16 years of experience
Bachelor's degree in Computer Science, Data Science, Engineering, IT, or a related field
Master's degree in Computer Science, Data Science, Engineering, IT, or a related field
Skills
Python
PyTorch
TensorFlow
scikit-learn
Hugging Face
MLflow
Kubeflow
Apache Airflow
AWS SageMaker
Azure AI/ML Services
Google Cloud Platform AI/ML Services
Docker
Kubernetes
CI/CD Pipelines
Model Registries
Experiment Tracking
Automated Testing
Deployment and Monitoring
LLMs
Prompt Engineering
RAG Architecture
Model Evaluation
Fine-tuning
Data Pipelines
Feature Stores
Data Quality
Data Lineage
Terraform
Pulumi
GitOps
Technical Leadership
Mentoring and Coaching
MLOps
ML Platform Engineering
Generative AI
Responsible AI
Model Explainability
Fairness Auditing and Bias Mitigation
Data Governance
Reliability Engineering
Cloud Cost Optimization
Security and Compliance
Next Steps
Shortlisted candidates will receive an email from with instructions to complete a required screening step. Completion of this screening is mandatory to be considered for the role.If you do not receive this email after applying, please contact our Talent Expert at
Company is a client operating in the public sector, supporting multiple state agencies through shared enterprise technology services. The organization focuses on delivering secure, scalable, and reliable AI/ML capabilities in a highly regulated government environment, with emphasis on responsible AI, cybersecurity, and privacy requirements aligned with standards such as FedRAMP and the NIST AI Risk Management Framework.
Key Responsibilities
Lead the architecture, development, implementation, and governance of a shared enterprise AI/ML platform supporting multiple state agencies
Deliver secure, scalable, reliable, and responsible AI/ML solutions across ML engineering, MLOps, cloud infrastructure, data engineering, and Generative AI
Build and operate shared enterprise AI/ML platforms supporting multiple teams or agencies
Establish MLOps practices including model registries, experiment tracking, automated testing, deployment, and monitoring
Design and manage data pipelines, feature stores, data quality, data lineage, and governance
Apply strong technical leadership in architecture, mentoring, security, and responsible AI
Ensure platform observability, reliability engineering, incident management, disaster recovery, and cloud cost optimization
Apply responsible AI practices including model explainability, fairness auditing, bias mitigation, and model risk management
Required Qualifications
16 years of experience
Bachelor's degree in Computer Science, Data Science, Engineering, IT, or a related field
Master's degree in Computer Science, Data Science, Engineering, IT, or a related field
Skills
Python
PyTorch
TensorFlow
scikit-learn
Hugging Face
MLflow
Kubeflow
Apache Airflow
AWS SageMaker
Azure AI/ML Services
Google Cloud Platform AI/ML Services
Docker
Kubernetes
CI/CD Pipelines
Model Registries
Experiment Tracking
Automated Testing
Deployment and Monitoring
LLMs
Prompt Engineering
RAG Architecture
Model Evaluation
Fine-tuning
Data Pipelines
Feature Stores
Data Quality
Data Lineage
Terraform
Pulumi
GitOps
Technical Leadership
Mentoring and Coaching
MLOps
ML Platform Engineering
Generative AI
Responsible AI
Model Explainability
Fairness Auditing and Bias Mitigation
Data Governance
Reliability Engineering
Cloud Cost Optimization
Security and Compliance
Next Steps
Shortlisted candidates will receive an email from with instructions to complete a required screening step. Completion of this screening is mandatory to be considered for the role.If you do not receive this email after applying, please contact our Talent Expert at