You will apply automated testing, evaluation, observability, security controls and production monitoring throughout the software delivery lifecycle.
You will prototype and rapidly iterate on solutions using data, user feedback and minimum viable implementations, then harden successful approaches for production.
You will review code and technical designs, provide constructive feedback, share knowledge and guide junior engineers toward stronger engineering practices.
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Candidates should possess effective Communication skills to collaborate with multidisciplinary teams, engage with clients, and present technical information clearly.
Relevant experience with IoT platforms, industrial automation, building management systems (BMS), or energy management solutions is beneficial.
A diploma or degree in Electrical Engineering, Mechatronics, Instrumentation, or a related field is preferred, along with proficiency in basic networking and familiarity with cloud-based data analytics.
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Field hero: Lead technical deployments on-site. When a high-profile client needs a custom solution in a factory or a mall, you’re the one who makes it happen.
Scaling: As we expand and add new humanoid brands to our fleet, you will lead the integration of their "brains" into our ecosystem.
A ROS2 Wizard who is comfortable living in the Linux terminal.
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Comfortable with numbers. Spreadsheets, dashboards, reading a report and asking why.
Can write a clean update that explains a result, not just reports a number.
Has built or tinkered with something of their own. A side project, a personal AI experiment, anything self-started. Doesn't need to be marketing related.
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Technical Leadership & Solution Ownership: Lead the technical direction of AI initiatives by driving architecture decisions, establishing best practices, mentoring team members, and guiding the end-to-end delivery of scalable AI solutions.
Collaboration & Delivery: Work with Product Owner, Developers, Quality Engineers and UX Designers to deliver the Virtual Companion. Contribute to sprint planning, code reviews and documentation.
Bachelor’s degree or above, with 5-8 years in software development and relevant experience in leading AI/ML development project
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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.