AI Engineer at HR Duo

HR Duo; Limerick; On-site; EUR 70,000 - 100,000; Full time

Job summary

HR Duo in Limerick (onsite) seeks an AI Engineer to design, build, and deploy practical AI solutions for manufacturing use cases. You will work with SMEs and partners to translate operational needs into grounded AI applications.

You will develop RAG-based systems, agentic workflows, and integrations with enterprise data, focusing on secure, scalable deployments in a regulated industrial context.

Qualifications

• Bachelor’s or Master’s in CS/DS/Engineering or equivalent practical experience.
• 2+ years in AI/engineering roles with hands-on development.
• Strong Python and software engineering practices (APIs, testing, version control).
• Experience with LLMs, RAG, embeddings, vector search, or agentic workflows.
• Experience integrating AI apps with databases, documents, APIs and operational systems.
• Familiarity with AWS/Azure/GCP, Docker and CI/CD fundamentals.
• Ability to communicate with non-technical stakeholders and SMEs.

Responsibilities

• Design and deploy production AI applications for manufacturing environments.
• Develop RAG solutions over SOPs, OCAPs, FMEAs, CAPAs and manuals with grounded responses.
• Build agentic workflows using tool calling and human approvals.
• Create APIs, services, and reusable components that integrate AI models with enterprise systems.
• Evaluate models, retrieval approaches, and AI services for quality, security, latency, and cost.
• Collaborate with SMEs to frame use cases, data types, and KPIs.

Skills

Python programming

APIs & testing

Version control

MLOps / model deployment

Non-technical stakeholder comms

Education

Bachelor’s or Master’s in CS/DS/Engineering

Tools

Docker

CI/CD

LLM APIs / embeddings / vector search

Job description

Apply for AI Engineer at HR Duo in Limerick, LK, IE. This Full time on site position offers great opportunities for career growth.

Company Information and Introduction:

Digital Manufacturing Ireland (DMI) is an industry-led organisation, supported by the Government of Ireland through IDA Ireland. Launched in 2023, DMI enables Irish-based manufacturers to access, adopt, and accelerate new digital technologies—solving real-world challenges and driving future competitiveness. DMI offers a state-of-the-art physical and digital factory, a vendor showcase, industry collaboration spaces, and training facilities. The DMI facility brings together technology, expertise, and business support to help manufacturing companies transform, innovate, and future-proof their operations.

Role Overview:

The AI Engineer will design, build and deploy practical AI solutions that help manufacturing organisations solve real operational challenges. The role will focus on applied generative & Agentic AI, including retrieval-augmented generation (RAG), AI assistants, agentic workflows and multimodal applications that connect securely with enterprise and manufacturing data. Working with manufacturing subject-matter experts and technology partners, this role will take use cases from discovery and rapid prototyping through evaluation and production deployment. This is a hands‑on role for someone who combines strong software engineering with.

Key Responsibilities and Duties:

• Applied Generative AI: Build production-ready AI applications including knowledge assistants, copilots and multimodal solutions.
• Design RAG solutions over manufacturing content such as SOPs, OCAPs, FMEAs, CAPAs and equipment manuals, producing grounded and traceable responses.
• Develop agentic workflows using tool calling, structured outputs and human approval steps where they add clear operational value.
• AI Engineering & Integration: Develop APIs, services and reusable components that integrate AI models with enterprise and manufacturing systems, databases and workflows.
• Evaluate and select models, retrieval approaches and AI services based on quality, security, latency, cost, maintainability and user needs.
• Production Delivery & Responsible AI: Deploy and operate AI services in AWS, Azure or GCP using appropriate containerisation, version control and CI/CD practices.
• Build evaluation and observability into AI solutions, monitoring response quality, groundedness, safety, performance, cost and user feedback.
• Apply guardrails, access controls, auditability, data‑protection practices and human oversight suitable for industrial and regulated settings.
• Manufacturing AI & Collaboration: Work on use cases such as yield analytics, anomaly detection, predictive maintenance and computer vision, integrating model outputs into usable applications and workflows.
• Collaborate with subject‑matter experts to frame use cases, understand structured and unstructured industrial data, define success measures and evaluate solutions against operational KPIs.
• Keep current with the evolving GenAI/agentic landscape and evaluates emerging models, frameworks and tools for practical fit.

Key Skills and Competencies:

Skills & Experience Required:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering or a related discipline - or equivalent practical experience.
• 2+ years of relevant experience in AI engineering, software engineering, applied AI, data science or a comparable hands‑on role.
• Strong Python skills and sound software engineering practices, including APIs, testing, version control and maintainable application design.
• Practical experience building with LLM APIs or open‑source models, including RAG, embeddings, vector search, structured outputs or agentic workflows.
• Experience integrating AI applications with databases, documents, APIs and operational systems.
• Familiarity with AWS, Azure or GCP, Docker and CI/CD fundamentals.
• Experience evaluating and monitoring AI systems for quality, reliability and safety.
• Able to translate operational needs into practical AI solutions with non‑technical stakeholders and subject‑matter experts.

Desirable Experience:

• Manufacturing, industrial or IoT environments and data sources, including MES, SCADA, historians, sensors, event logs or industrial image data.
• Machine learning or computer vision using TensorFlow, PyTorch or scikit‑learn; exposure to industrial inspection, edge AI, digital twins, simulation or reinforcement learning.
• Experience in regulated or manufacturing sectors such as medtech, pharma, food or discrete manufacturing.