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INTERLOCK SECURITY AND INVESTIGATION SERVICES PTE LTD

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Gen AI Engineer

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Summary

Builds generative-AI capabilities for humanoid and autonomous security robots: multimodal AI agents, agentic/advanced RAG pipelines, and LLM/VLM integration with robotic control systems. Core stack includes Python, FastAPI, LangGraph/AutoGen, ROS/ROS2, vector databases, and AWS, Azure or GCP.

Job Requirements

Humanoid Robotics & Physical AI

Develop and integrate AI capabilities into humanoid and autonomous robotic systems.

Build multimodal AI agents supporting voice, vision, natural language understanding and human robot interaction.

Develop intelligent task planning, reasoning, decision-making and robotic workflow orchestration.

Integrate LLMs and Vision-Language Models (VLMs) with robotic control systems.

Work with robotics frameworks such as ROS/ROS2, Python and robot SDKs.

Support robotic perception, navigation, manipulation and autonomous task execution in collaboration with robotics engineers.

Integrate robots with Digital Twin platforms, IoT systems and Smart Command Centres.

Relevant Technical Skills

Generative AI: LLMs, Prompt Engineering, Fine-tuning, Agentic RAG and Advanced RAG Pipelines.

AI Agents: Multi-Agent Systems, LangGraph, AutoGen and AI workflow orchestration.

AI Security: LLM Guardrails, Responsible AI, Governance, Evaluation and Compliance.

Multimodal AI: Text, Voice, Vision, Conversational AI and Vision-Language Models.

Robotics AI: ROS/ROS2, Robot SDKs, Vision-Language-Action (VLA) Models, Robot Perception and Physical AI.

AI Operations: LLMOps, AI Monitoring, Observability, Model Evaluation and Deployment.

Cloud Platforms: AWS, Microsoft Azure or Google Cloud Platform.

Programming & Integration: Python, FastAPI, REST APIs, Vector Databases and LLM Frameworks.

Candidate Requirements

Minimum 2 years of relevant experience in GenAI, LLM applications, AI automation or related AI engineering.

Strong Python programming and API integration skills.

Experience developing and deploying AI agents or production-grade AI applications.

Good understanding of AI model evaluation, performance, security and scalability.

Experience in digital marketing automation or humanoid robotics will be an added advantage.

Ability to work independently and collaborate with multidisciplinary engineering teams.

Skills

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See also

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