Sr. Data Engineer

Oteemo Inc.; Virginia (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

Oteemo Inc. seeks 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 data pipelines across polyglot client environments, develop Generative AI, ML and BI systems, and implement MLOps/LLMOps across AWS, Azure, and GCP.

You will mentor junior engineers, enforce security and governance, and drive reliable software engineering practices within the team.

Qualifications

• Experience building scalable data pipelines in Python/SQL.
• Strong knowledge of GenAI, LLMs, and agentic workflows.
• Hands-on MLOps/LLMOps across cloud platforms.
• Experience with data security, PHI/PII governance.
• Mentor junior engineers and drive best practices.

Responsibilities

• Design and implement AI features end to end, applying sound judgment on model behavior and guardrails.
• Build and optimize scalable, secure data pipelines and ETL/ELT workflows.
• Develop Generative AI, agentic, ML, and BI systems using modern frameworks.
• Implement MLOps/LLMOps — CI/CD for data workflows and IaC across cloud providers.
• Enforce data security and governance, mentoring the team on best practices.

Skills

AI/ML Systems

Data Pipelines

Python/SQL

Cloud Platforms

MLOps

GenAI/LLM

Vector Databases

Spark

LangChain

Data Security

Tools

Spark

Databricks

Airflow

LangChain

Job description

We're looking for a Senior Data Engineer to design and implement AI features end to end — from data pipelines through GenAI and agentic workflows to production deployment. In this role, you'll build and optimize scalable, secure data pipelines across polyglot client enterprise environments, develop Generative AI, agentic, ML, and BI systems using modern frameworks, and implement MLOps/LLMOps practices across AWS, Azure, and GCP. You'll own technical workstreams autonomously, mentor junior engineers, and bring sound judgment on model behavior, evaluation, reliability, and guardrails to everything you build.

Responsibilities:

• Help design and implement AI features end to end — from data pipelines through GenAI/agentic workflows to production deployment — applying sound judgment on model behavior, evaluation, reliability, and guardrails.
• Build and optimize scalable, secure data pipelines and ETL/ELT workflows in Python and SQL across polyglot client enterprise environments.
• Develop Generative AI, agentic, ML, and BI systems using RAG, embeddings, vector databases, and modern frameworks (Spark, LangChain, Databricks, Airflow, and similar).
• Implement MLOps/LLMOps practices — CI/CD for data workflows, automated agent evaluation, and infrastructure as code across AWS, Azure, and GCP.
• Enforce data security and governance, including PII/PHI handling, authentication, and role-based access control.
• Own technical workstreams autonomously, mentor junior engineers, and champion software engineering best practices across the team.