OverviewInabia is seeking an AI Engineer to design, build, and deploy advanced large language model solutions and retrieval-augmented generation (RAG) pipelines integrated into enterprise cloud environments. This role demands deep hands-on expertise in leading LLM frameworks alongside the communication skills necessary to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders. Candidates with manufacturing domain experience are strongly encouraged to apply.
Responsibilities- Architect end-to-end RAG pipelines leveraging Hugging Face, LangChain, and OpenAI API to solve enterprise-scale challenges.
- Integrate generative AI capabilities into existing enterprise cloud environments and data infrastructure.
- Develop, fine-tune, and evaluate large language models for domain-specific use cases.
- Write production-quality code in Python, R, and SQL to support data ingestion, model serving, and analytics workflows.
- Translate complex model outputs and analytical findings into clear, actionable recommendations for operational and executive stakeholders.
- Collaborate cross-functionally with engineering, operations, and leadership teams to identify and prioritize high-impact AI use cases.
- Monitor model performance, troubleshoot issues, and continuously improve pipeline reliability and accuracy.
- Document architectures, methodologies, and outcomes to support knowledge transfer and reproducibility.
Key Qualifications- 5+ years of experience as an AI/ML Engineer (exceptional candidates with more experience are equally welcome).
- Hands-on proficiency with LLM/AI frameworks: Hugging Face, LangChain, and OpenAI API.
- Demonstrated experience architecting and deploying RAG pipelines in production environments.
- Strong programming skills in Python, R, and SQL.
- Proven ability to communicate technical concepts and model results to non-technical operations and executive audiences.
- Experience integrating AI solutions into enterprise cloud platforms.
Preferred Qualifications- 2-4 years of experience working in a manufacturing domain.
- Familiarity with shop floor operations, production planning, and systems such as MES, SCADA, and ERP.
- Proficiency in industrial communication protocols (OPC-UA, MQTT, Modbus) with demonstrated ability to bridge OT/IT systems for real-time data extraction.
- Applied experience with OEE, Six Sigma, SPC, and lean manufacturing methodologies to drive measurable improvements in yield, uptime, and operational efficiency.
