• C4135D Data Scientist V

    ManpowerGroup (Columbus, OH)


    **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

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

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

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

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

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

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

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

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

    9. Document design patterns, integration frameworks, and operational playbooks.

    Required Skills & Qualifications

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

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

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

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

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

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

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

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

    Preferred Qualifications

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

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

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

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

    5. 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.