Senior GenAI Engineer: LLMs, RAG Pipelines & Agents

Openkrill; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Openkrill is seeking a senior Data Science/AI engineer to lead GenAI architecture and solution design in a fast-moving environment. You will translate business problems into robust, scalable AI systems, building end-to-end GenAI applications with data ingestion, retrieval, and orchestration components.

You will improve RAG pipelines, perform model selection and fine-tuning, and implement safety and governance controls while collaborating with cross-functional teams and mentoring peers.

Qualifications

• 6+ years in Data Science/AI engineering.
• 4+ years producing production-ready Python AI code.
• 2+ years in production-ready LLM code, preferably RAG-based.

Responsibilities

• Lead discovery and solution design for GenAI use cases, translating business problems into architectures.
• Build end-to-end GenAI applications including data ingestion, retrieval, orchestration, API/backend, and UI.
• Design and implement RAG pipelines with vector databases and hybrid search.
• Perform model selection, prompting strategies, and fine-tuning for multiple modalities.
• Implement safety, governance, and audit controls; ensure compliance.
• Collaborate with data engineers, product owners, and full-stack developers on scalable architectures.
• Mentor other data scientists/engineers and contribute to internal libraries and templates.
• Stay current with GenAI trends and run PoCs to validate new approaches.

Skills

Data Science

Python

LLMs

GenAI frameworks

Cloud platforms

Tools

LangChain

LlamaIndex

LangGraph

Job description

Openkrill is seeking a senior Data Science/AI engineer to lead GenAI architecture and solution design in a fast-moving environment. You will translate business problems into robust, scalable AI systems, building end-to-end GenAI applications with data ingestion, retrieval, and orchestration components.

You will improve RAG pipelines, perform model selection and fine-tuning, and implement safety and governance controls while collaborating with cross-functional teams and mentoring peers.