Integrate and configure sensors, actuators, motion control systems, PLCs, HMIs, and machine vision systems to deliver reliable and cohesive automation solutions.
Lead system integration, testing, commissioning, debugging, and optimization activities at the company and customer sites.
Analyze complex control system issues, identify root causes, and implement effective corrective and preventive solutions to improve system reliability and performance.
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Adapt and tailor technology solutions to ensure compliance with regional requirements, including security practices, data regulations and other local needs
Provide ongoing technical support and expertise to regional users, ensuring high system performance and minimizing operational disruptions
Contribute to the full application lifecycle, from initial concept and development through to deployment and ongoing maintenance and support
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Translate complex algorithmic ideas - syntax parsing, semantic chunking, custom routing - into reliable, production ready software components.
Build and rigorously evaluate prototypes for future AI initiatives, including open source small language models (SLMs), custom embeddings, and multi agent / cross validation patterns, backed by measurable retrieval and quality metrics.
Architect multi tenant data, identity, and authorization layers that meet enterprise security and compliance requirements.
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Understand the system design and provide impact analysis to any changes.
Perform application health check and monitoring
Required to work on shifts on a rotational basis to provide 18 by 7 support with 2 days off. (9 hours per shift – 6:30am to 3:30pm/ 2:30pm to 11:30pm)
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Assess the commercial potential and technical readiness levels of internal R&D projects for potential spin-offs or new business incubation.
Bachelor's degree in Engineering (e.g., Electrical, Mechanical, Chemical, Software, Materials Science, Biomedical) or a relevant scientific discipline from an accredited institution.
Master's or Ph.D. in a relevant engineering or scientific field is highly preferred.
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Job SummaryWe are looking for a hands-on AI Engineer to design, develop, integrate, and deploy Generative AI, AI chatbot, and Agentic AI solutions. The role will focus on building practical AI applications and integrating LLM capabilities with existing applications, APIs, databases, and enterprise systems.Key ResponsibilitiesDesign and develop AI chatbots, copilots, and LLM-powered applications.Build Agentic AI solutions with reasoning, tool/function calling, multi-step task execution, and workflow automation.Implement RAG, embeddings, vector search, prompt engineering, and conversational memory.Work with commercial and open-source LLMs and select appropriate models based on business and technical requirements.Integrate AI solutions with REST APIs, databases, CRM/ERP systems, and enterprise applications.Develop AI integration services and APIs for existing systems and business workflows.Evaluate and optimize AI solutions for accuracy, reliability, latency, scalability, security, and cost.Collaborate with software engineers, architects, product teams, and business stakeholders.Keep up to date with developments in Generative AI, LLMs, Agentic AI, and AI automation.RequirementsBachelor's degree in Computer Science, AI/ML, Software Engineering, or a related field.3+ years of experience in AI/ML engineering, software engineering, or a related role.Hands-on experience developing LLM applications, AI chatbots, or Generative AI solutions.Practical experience with AI Agents, Agentic AI, tool/function calling, or AI workflow automation.Experience with open-source LLMs such as Llama, Qwen, Mistral, Gemma, or equivalent.Strong Python programming and software engineering skills.Experience with REST APIs, system integration, databases, and cloud/on-premise environments.Hands-on experience with RAG, vector databases, embeddings, and prompt engineering.Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent.Experience with LLM platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, and/or open-source models.Familiarity with Docker, Git, CI/CD, and production deployment.Preferred SkillsExperience serving open-source LLMs using vLLM, Hugging Face, Ollama, or equivalent.Experience with MCP, multi-agent systems, LLM evaluation/observability, fine-tuning, LoRA/QLoRA, or model optimization.Experience with AWS, Azure, or Google Cloud.Knowledge of AI security, data privacy, access control, and responsible AI.