Data Scientist V

Position Title : (2) Data Engineer - LLM & Generative AI Integration

Location : Columbus OH

Role : 3 month contract

Rate : 80hr

Citizenship : US Citizens

Interviews : will be on-site

Position 1 - will be integrating large language models and generative AI systems into the environment.

• Mandatory skills needed : Databricks, Azure, Cloud Computing, Python, SQL, Semantic Kernal or Llamaindex.

Position 2 - will be creating the data pipelines from beginning to end. Transforming the data, getting it ready for AI.

Mandtory skills : CI / CD pipeline experience, Azure Databricks, SQL, Python.

This one will communicate more with business users, so will need good communication / collaboration skills.

Overview

We are looking for an innovative Data Engineer to lead the integration of Large Language Models (LLMs) and Generative AI systems within our enterprise data ecosystem. This role focuses on designing, automating, and optimizing data pipelines and interfaces that connect curated enterprise data with advanced AI models. You will bridge the gap between data engineering and AI innovation , delivering secure, scalable, and high-performance systems that power next-generation language-driven applications.

Key Responsibilities

Design, build, and optimize data pipelines supporting LLM-powered systems and AI applications.

Integrate Generative AI and LLM technologies (OpenAI, Anthropic, Azure OpenAI, LLaMA, Mistral, etc.) with enterprise data sources.

Develop and maintain Retrieval-Augmented Generation (RAG) pipelines connecting structured and unstructured data to model contexts.

Collaborate with data scientists, ML engineers, and AI researchers to align data quality with model performance.

Implement agentic system architectures and orchestration frameworks (LangChain, Semantic Kernel, or similar).

Enforce AI security, governance, and compliance best practices for responsible data use.

Automate LLM evaluation, fine-tuning, and deployment workflows where applicable.

Monitor and troubleshoot AI data pipelines for performance, accuracy, and scalability.

Document design patterns, integration frameworks, and operational playbooks.

Required Skills & Qualifications

Proven experience as a Data Engineer or ML Engineer working with LLM or Generative AI integrations.

Strong programming skills in Python, SQL , and distributed data frameworks ( Spark, Databricks ).

Hands-on experience with RAG architectures , vector databases (Pinecone, Weaviate, Chroma, FAISS), and embedding pipelines.

Familiarity with frameworks such as LangChain, LlamaIndex, and Semantic Kernel .

Knowledge of AI security and privacy , including prompt injection prevention and data governance.

Solid understanding of cloud-based AI infrastructure , preferably Azure AI Services, Azure Databricks, and Azure OpenAI Service .

Strong problem-solving skills and ability to collaborate across data, infrastructure, and AI teams.

Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).

Preferred Qualifications

Experience fine-tuning or customizing LLMs for enterprise use cases.

Familiarity with MLflow, MLOps , and CI / CD pipelines for model deployment.

Knowledge of medallion data architecture and Delta Lake for AI-ready data management.

Experience with real-time data systems (Kafka, Event Hubs) for streaming AI applications.

Contributions to open-source AI projects or enterprise AI integrations .

ManpowerGroup is committed to providing equal employment opportunities in a professional, high quality work environment. It is the policy of ManpowerGroup and all of its subsidiaries to recruit, train, promote, transfer, pay and take all employment actions without regard to an employee's race, color, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, religion, age, disability, protected veteran status, or any other basis protected by applicable law.