Senior AI Data Engineer — GenAI & MLOps Architect

Oteemo; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Oteemo 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’ll 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, while enforcing data security and governance, including RBAC and PII/PHI handling.

Qualifications

• Active Secret or Top Secret clearance required.
• 5+ years of data engineering experience leading technical workstreams and mentoring engineers.
• Expert Python and SQL proficiency; ability to work in polyglot environments (Scala/Java).
• Experience building Agentic AI, Generative AI, ML, and BI systems with modern frameworks (Spark, LangChain, Databricks, Airflow).
• Ability to lead end-to-end AI feature development with attention to reliability and guardrails.

Responsibilities

• Design and implement AI features end to end — from data pipelines through GenAI/agentic workflows to production deployment.
• Build scalable, secure data pipelines and ETL/ELT workflows in Python and SQL across polyglot client environments.
• Develop Generative AI, agentic, ML, and BI systems using RAG, embeddings, vector databases, and modern frameworks (Spark, LangChain, Databricks, Airflow).
• Implement MLOps/LLMOps practices — CI/CD for data workflows, automated agent evaluation, IaC across AWS, Azure, GCP.
• Enforce data security and governance, including PII/PHI handling, authentication, and RBAC.
• Own technical workstreams autonomously, mentor junior engineers, and promote engineering best practices.

Skills

Python

SQL

Scala/Java

MLOps/LLMOps

Data engineering

Security RBAC

Cloud platforms

Tools

Spark

Databricks

Airflow

LangChain

Kedro

Dagster

Job description

Oteemo 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’ll 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, while enforcing data security and governance, including RBAC and PII/PHI handling.