AI & Data Engineer
Ai Engineering
Ai Ml
Api Integration
Artificial Intelligence
Cloud Operations
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Pipeline
Data Platform
Data Processing
Database
Databases
ETL
Etl Pipeline
Generative AI
Informatica
Information Technology (IT)
Large Language Models
Machine Learning
Programming
Programming Language
Programming Languages
Prompt Engineering
Rag Architectures
SQL
Job Description
The AI & Data Engineer at EVERFORCE LLC will design, build, and maintain scalable data pipelines and ETL/ELT processes, and will develop and operate AI/ML models in production environments. The role also supports integration with enterprise systems and cloud platforms, along with documentation and governance-focused deliverables.
Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows to ingest, clean, transform, and integrate structured and unstructured data from enterprise systems and other data sources.
- Develop, train, test, and deploy machine learning and artificial intelligence models, including integration of large language models (LLMs) where applicable. Support prompt engineering and retrieval-augmented generation (RAG) pipelines as needed.
- Integrate AI/ML models and data pipelines with enterprise applications, APIs, and cloud-based platforms.
- Monitor, troubleshoot, and optimize performance, quality, and reliability of data pipelines and models. Include data validation and resolution of data or model issues.
- Maintain documentation, metadata, and data lineage to support governance, transparency, and auditability.
- Collaborate with IT, data science, and business teams to gather requirements, refine solutions, and support ongoing AI and data initiatives.
Technologies
- ETL/ELT
- Machine learning
- Artificial intelligence
- Large language models (LLMs)
- Prompt engineering
- Retrieval-augmented generation (RAG)
- APIs
- Cloud-based platforms
Deliverables
- Documented, production-ready data pipelines and ETL/ELT jobs, including source-to-target mapping and data quality checks.
- Trained, validated, and deployed AI/ML models (or model enhancements), along with relevant performance and evaluation metrics.
- Integrations connecting AI/ML models and data pipelines to enterprise systems, applications, and/or cloud platforms.
- Dashboards, reports, or monitoring tools to track data quality, pipeline health, and/or model performance.
- Technical documentation covering data pipeline architecture, data lineage, model design, and deployment processes.
- Periodic status updates and knowledge-transfer materials for IT and business teams.
Location and Compensation
Location: Santa Clara, CA (onsite)
Salary: USD 110,000 - 150,000 per year
Experience
Minimum experience: 2 years
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