PSI (Proteam Solutions)
We are seeking an experienced Data or ML Engineer to design, build, and operationalize intelligent data pipelines that power large language models (LLM) and generative AI systems. This role bridges the gap between data engineering and AI innovation, enabling secure, scalable, and high‑performance integration of enterprise data with advanced language models.
Work Setup
Position Type: Contract (6 months, likely to extend or convert).
Work Location: Onsite – Columbus, OH (Local or willing to relocate Day 1).
Work Authorization: Must be authorized to work in the United States without sponsorship.
Industry: Research and Advanced Technology.
Key Responsibilities
Design and optimize data pipelines serving LLM and generative AI applications.
Integrate generative AI systems (e.g., OpenAI, Azure OpenAI, Anthropic, LLaMA, Mistral) with curated enterprise data sources.
Develop and maintain retrieval-augmented generation (RAG) pipelines connecting structured and unstructured data to AI model contexts.
Collaborate with data scientists, ML engineers, and AI researchers to ensure data readiness and model efficiency.
Implement agentic system architectures using frameworks like LangChain, Semantic Kernel, or LlamaIndex.
Apply best practices in AI security, data governance, and compliance to ensure responsible AI development.
Automate LLM evaluation, fine‑tuning, and deployment workflows while maintaining high system availability and accuracy.
Required Skills & Qualifications
Proven experience as a Data Engineer or ML Engineer integrating LLM or generative AI systems.
Proficiency in Python, SQL, and distributed data frameworks such as Spark or Databricks.
Strong understanding of RAG architectures and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).
Experience with orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
Understanding of AI security, data privacy, and prompt injection defenses.
Experience working with Azure Databricks, Azure AI Services, or Azure OpenAI.
Strong collaboration, problem‑solving, and communication skills.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Preferred Qualifications
Experience fine‑tuning or customizing LLMs for enterprise use cases.
Familiarity with MLflow, MLOps, or CI/CD for AI model deployment.
Understanding of Delta Lake or Medallion data architecture for AI‑ready pipelines.
Experience with streaming systems such as Kafka or Event Hubs.
Contributions to open‑source AI or LLM integration projects.
Why This Role Is a Great Opportunity
Contribute to next‑generation AI innovation within a globally recognized research and technology organization.
Work hands‑on with cutting‑edge technologies—LLMs, generative AI, RAG pipelines, and orchestration frameworks—to power real‑world data intelligence systems.
Collaborate with top data scientists and AI researchers in a mission‑driven environment that values innovation and long‑term impact.
Onsite position in Columbus, OH with the potential for long‑term extension or conversion to a permanent role.
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Work Setup
Position Type: Contract (6 months, likely to extend or convert).
Work Location: Onsite – Columbus, OH (Local or willing to relocate Day 1).
Work Authorization: Must be authorized to work in the United States without sponsorship.
Industry: Research and Advanced Technology.
Key Responsibilities
Design and optimize data pipelines serving LLM and generative AI applications.
Integrate generative AI systems (e.g., OpenAI, Azure OpenAI, Anthropic, LLaMA, Mistral) with curated enterprise data sources.
Develop and maintain retrieval-augmented generation (RAG) pipelines connecting structured and unstructured data to AI model contexts.
Collaborate with data scientists, ML engineers, and AI researchers to ensure data readiness and model efficiency.
Implement agentic system architectures using frameworks like LangChain, Semantic Kernel, or LlamaIndex.
Apply best practices in AI security, data governance, and compliance to ensure responsible AI development.
Automate LLM evaluation, fine‑tuning, and deployment workflows while maintaining high system availability and accuracy.
Required Skills & Qualifications
Proven experience as a Data Engineer or ML Engineer integrating LLM or generative AI systems.
Proficiency in Python, SQL, and distributed data frameworks such as Spark or Databricks.
Strong understanding of RAG architectures and vector databases (e.g., Pinecone, Weaviate, Chroma, FAISS).
Experience with orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
Understanding of AI security, data privacy, and prompt injection defenses.
Experience working with Azure Databricks, Azure AI Services, or Azure OpenAI.
Strong collaboration, problem‑solving, and communication skills.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Preferred Qualifications
Experience fine‑tuning or customizing LLMs for enterprise use cases.
Familiarity with MLflow, MLOps, or CI/CD for AI model deployment.
Understanding of Delta Lake or Medallion data architecture for AI‑ready pipelines.
Experience with streaming systems such as Kafka or Event Hubs.
Contributions to open‑source AI or LLM integration projects.
Why This Role Is a Great Opportunity
Contribute to next‑generation AI innovation within a globally recognized research and technology organization.
Work hands‑on with cutting‑edge technologies—LLMs, generative AI, RAG pipelines, and orchestration frameworks—to power real‑world data intelligence systems.
Collaborate with top data scientists and AI researchers in a mission‑driven environment that values innovation and long‑term impact.
Onsite position in Columbus, OH with the potential for long‑term extension or conversion to a permanent role.
#J-18808-Ljbffr