Not Applicable
Posted April 2, 2026
Job link
Thinking about this job
Responsibilities
Responsibilities
- requirements and inform system architecture decisions
- System security and networking (particularly the implementation of system
- security on classified systems)
- Data engineering and data lifecycle management
Not Met Priorities
What still needs stronger evidence
Requirements
- Active TS/SCI W/ Polygraph Required.
- engineering experience.
- engineering experience.
- OR
- from an accredited college or university plus five (5) years of systems
- engineering experience.
- accredited college or university plus three (3) years of systems
- engineering experience.
- Cloud Architecture/ Cloud Engineer/ Platform Engineering (especially in AWS)
- AI/ML system design and implementation
- High-level understanding of the AI lifecycle (development, training,
- inference, monitoring)
- Experience with ML pipeline development, model deployment, and
- DevOps/MLOps
- Excellent communication and collaboration skills with a variety of stakeholder
- groups, ability to proactively engage with these groups to understand
- requirements and inform system architecture decisions
- System security and networking (particularly the implementation of system
- security on classified systems)
- Data engineering and data lifecycle management
Preferred Skills
- Experience with ML pipeline development, model deployment, and
- DevOps/MLOps
- Experience with Amazon SafeMaker is a plus
- groups, ability to proactively engage with these groups to understand
- requirements and inform system architecture decisions
- System security and networking (particularly the implementation of system
- security on classified systems)
- Data engineering and data lifecycle management
Education
- (Not required) – A High School Diploma or GED plus twelve (12) years of general system
- (Not required) – OR
- (Not required) – A Bachelor’s degree in a Qualified Engineering Field or a related discipline
- (Not required) – from an accredited college or university plus seven (7) years of systems
- (Not required) – engineering experience.
- (Not required) – OR
- (Not required) – A Master’s degree in a Qualified Engineering Field or a related discipline
- (Not required) – from an accredited college or university plus five (5) years of systems
- (Not required) – engineering experience.
- (Not required) – OR
- (Not required) – A PhD in a Qualified Engineering Field or a related discipline from an
- (Not required) – accredited college or university plus three (3) years of systems
Serving Maryland and the Greater Washington D.C. area, SageCor Solutions (SageCor) is a growing company bringing complete engineering services and true full lifecycle System Engineering services to areas requiring (or desiring) nationally-recognized expertise in high performance computing, large data analytics and cutting edge information technologies.
Active TS/SCI W/ Polygraph Required.
Required Experience:
A High School Diploma or GED plus twelve (12) years of general system
engineering experience.
OR
A Bachelor’s degree in a Qualified Engineering Field or a related discipline
from an accredited college or university plus seven (7) years of systems
engineering experience.
OR
A Master’s degree in a Qualified Engineering Field or a related discipline
from an accredited college or university plus five (5) years of systems
engineering experience.
OR
A PhD in a Qualified Engineering Field or a related discipline from an
accredited college or university plus three (3) years of systems
engineering experience.
Position Details:
Cloud Architecture/ Cloud Engineer/ Platform Engineering (especially in AWS)
AI/ML system design and implementation
High-level understanding of the AI lifecycle (development, training,
inference, monitoring)
Experience with ML pipeline development, model deployment, and
DevOps/MLOps
Experience with Amazon SafeMaker is a plus
Excellent communication and collaboration skills with a variety of stakeholder
groups, ability to proactively engage with these groups to understand
requirements and inform system architecture decisions
System security and networking (particularly the implementation of system
security on classified systems)
Data engineering and data lifecycle management
Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.
Active TS/SCI W/ Polygraph Required.
Required Experience:
A High School Diploma or GED plus twelve (12) years of general system
engineering experience.
OR
A Bachelor’s degree in a Qualified Engineering Field or a related discipline
from an accredited college or university plus seven (7) years of systems
engineering experience.
OR
A Master’s degree in a Qualified Engineering Field or a related discipline
from an accredited college or university plus five (5) years of systems
engineering experience.
OR
A PhD in a Qualified Engineering Field or a related discipline from an
accredited college or university plus three (3) years of systems
engineering experience.
Position Details:
Cloud Architecture/ Cloud Engineer/ Platform Engineering (especially in AWS)
AI/ML system design and implementation
High-level understanding of the AI lifecycle (development, training,
inference, monitoring)
Experience with ML pipeline development, model deployment, and
DevOps/MLOps
Experience with Amazon SafeMaker is a plus
Excellent communication and collaboration skills with a variety of stakeholder
groups, ability to proactively engage with these groups to understand
requirements and inform system architecture decisions
System security and networking (particularly the implementation of system
security on classified systems)
Data engineering and data lifecycle management
Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.