Senior AI Data Engineer – GenAI & MLOps

Oteemo, Inc; Virginia (IL); On-site; USD 140,000 - 200,000; Full time

Job summary

Oteemo, Inc. is seeking a Senior Data Engineer to design and implement AI features end to end—from data pipelines through GenAI and agentic workflows to production deployment.

You will build scalable, secure data pipelines across polyglot client environments and develop Generative AI, agentic, ML, and BI systems using modern frameworks. You will implement MLOps/LLMOps practices across AWS, Azure, and GCP, enforce data security and governance, and own technical workstreams autonomously while

Qualifications

• 5+ years of professional data engineering experience including leading technical workstreams.
• Expert-level Python and SQL; able to work in polyglot environments (Scala, Java).
• Strong experience building Agentic AI, Generative AI, ML, and BI systems (RAG, embeddings, vector DBs).
• Experience with MLOps/LLMOps including CI/CD for data workflows and automated evaluation.

Responsibilities

• Design and implement AI features end to end from data pipelines to production deployment.
• Build and optimize scalable, secure data pipelines and ETL/ELT workflows.
• Develop AI/ML/BI systems using modern frameworks (Spark, LangChain, Databricks, Airflow).
• Implement MLOps/LLMOps practices across AWS, Azure, GCP.
• Enforce data security and governance, including PII/PHI handling and RBAC.
• Own technical workstreams autonomously and mentor junior engineers.

Skills

Python

SQL

Agentic AI

Generative AI

MLOps/LLMOps

RBAC

Cloud platforms

Problem solving

Mentoring

Time management

Tools

Spark

LangChain

Databricks

Airflow

Terraform

Job description

Oteemo, Inc. is seeking a Senior Data Engineer to design and implement AI features end to end—from data pipelines through GenAI and agentic workflows to production deployment.

You will build scalable, secure data pipelines across polyglot client environments and develop Generative AI, agentic, ML, and BI systems using modern frameworks. You will implement MLOps/LLMOps practices across AWS, Azure, and GCP, enforce data security and governance, and own technical workstreams autonomously while