Junior AI Engineer
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Key details
- Location
- Omaha, NE, United States
- Work style
- Remote
- Level
- Entry level
- Experience
- 1–3 yrs
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- 16h ago
Skills
data engineeringdata ingestiondata pipelinesfund administrationmachine learningmlopspythonsql
About the role
Position Summary
The Junior AI Engineer will assist in the development and maintenance of enterprise AI infrastructure. The role will partner with senior engineers to build data pipelines, deploy models, and ensure AI investments are technically sound. The role requires a detail-oriented builder who can execute technical tasks efficiently and collaborate with cross-functional technical teams.
Key Responsibilities
Assist in building and maintaining secure data pipelines for financial data ingestion
Write, test, and deploy production-ready code to support AI integrations across core workflows
Monitor live machine learning models in production environments and troubleshoot technical bottlenecks
Collaborate with AI Developers to expose AI functionalities via internal APIs
Track technical KPIs tied to code quality, deployment speed, and system stability
Qualifications
1–3 years of experience in software engineering, data engineering, or a related technical role
Demonstrated ability to write clean, efficient code and learn new frameworks quickly
Proficiency in programming languages such as Python and SQL
Ability to work effectively with technical teams and follow MLOps best practices
Experience in financial services or fund administration preferred but not required
Strong problem-solving skills and technical curiosity
Operator mindset with a focus on execution and technical reliability
The Junior AI Engineer will assist in the development and maintenance of enterprise AI infrastructure. The role will partner with senior engineers to build data pipelines, deploy models, and ensure AI investments are technically sound. The role requires a detail-oriented builder who can execute technical tasks efficiently and collaborate with cross-functional technical teams.
Key Responsibilities
Assist in building and maintaining secure data pipelines for financial data ingestion
Write, test, and deploy production-ready code to support AI integrations across core workflows
Monitor live machine learning models in production environments and troubleshoot technical bottlenecks
Collaborate with AI Developers to expose AI functionalities via internal APIs
Track technical KPIs tied to code quality, deployment speed, and system stability
Qualifications
1–3 years of experience in software engineering, data engineering, or a related technical role
Demonstrated ability to write clean, efficient code and learn new frameworks quickly
Proficiency in programming languages such as Python and SQL
Ability to work effectively with technical teams and follow MLOps best practices
Experience in financial services or fund administration preferred but not required
Strong problem-solving skills and technical curiosity
Operator mindset with a focus on execution and technical reliability