AI Engineer GenAI & Agentic AI

About the Role

We are looking for an AI Engineer specializing in GenAI & Agentic AI to develop innovative solutions within our global EMS operations. You will work on business, operations, engineering, and manufacturing use cases using cutting-edge technologies.

Key Responsibilities:

• Develop AI applications and POCs across various business domains.
• Build Generative AI solutions leveraging LLMs such as GPT, Claude, Gemini, Llama, Phi, or similar models.
• Create RAG (Retrieval-Augmented Generation) solutions utilizing company documents, databases, and enterprise knowledge.
• Design and develop AI agents and agentic workflows for multi-step business tasks, decision-making, and tool/API usage integration.
• Integrate AI solutions with REST APIs, databases, enterprise applications, and approved tools.
• Develop human-in-the-loop workflows for validation, approval, and exception handling.
• Build backend services, data-processing workflows, and supporting APIs for AI applications.
• Evaluate AI models based on accuracy, reliability, performance, cost, and security.
• Leverage Microsoft Azure AI, Microsoft Foundry, Azure OpenAI, or other suitable platforms.
• Develop and deploy AI applications using Docker in cloud or on-premise environments.
• Conduct technical feasibility studies, rapid prototyping, POCs, testing, and deployment activities.
• Collaborate with cross-functional teams including business, IT, software engineering, and other technical departments to deliver practical AI solutions.
• Prepare solution architecture documentation, technical reports, and POC/evaluation findings.
• Continuously explore emerging Generative AI, Agentic AI models, frameworks, and trends.

Requirements:

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Electronics, IT, or a related field.
• 2–5 years of experience in AI engineering, software engineering, Generative AI, or related application development.
• Strong hands-on proficiency in Python and software development practices.
• Practical experience with LLMs, RAG architectures, embeddings, vector databases, semantic search, and knowledge retrieval systems.
• Demonstrated experience developing AI agents, agentic workflows, tool/function calling mechanisms, or multi-step AI applications.
• Familiarity with frameworks such as Microsoft Agent Framework, Semantic Kernel, LangGraph, or equivalent technologies.
• Strong proficiency in REST APIs, SQL databases, and system integration methodologies.
• Experience with Git version control, Docker containerization, Linux environments, CI/CD pipelines, and cloud/on-premise deployment strategies.
• Preferrable familiarity with Microsoft Azure, Microsoft Foundry, or Azure OpenAI ecosystems.
• Understanding of AI evaluation metrics, structured outputs generation, prompt engineering techniques, hallucination mitigation strategies, and responsible AI principles.
• Strong problem-solving skills enabling the conversion of business requirements into practical AI solutions.
• Excellent communication skills facilitating effective collaboration with both technical and non-technical stakeholders.
• Capability to independently take an AI use case from initial assessment and architecture through POC, evaluation phases, and final deployment.
• Exposure to computer vision applications, manufacturing processes, engineering contexts, automation systems, or robotics is highly valued.
• A demonstrated willingness to continuously learn and experiment with emerging AI technologies.