Senior Agentic AI / RAG Engineer

Role Overview We are looking for aSenior Agentic AI / RAG Engineerto build intelligent robotic systems powered byLLMs, Agentic AI, and real-world perception pipelines . This role focuses on enabling robots toreason, plan, and act autonomouslyby combiningRAG-based knowledge systems with robotics frameworks (ROS, sensors, control systems) . You will bridgeAI cognition (LLMs)withphysical execution (robots) . Key Responsibilities Designagentic AI architectures for robotics(planning, reasoning, tool usage in real-world tasks) BuildRAG pipelinesto enable robots to query knowledge (manuals, environment data, SOPs) Integrate LLMs withrobotics stacks (ROS/ROS2)for decision-making and task planning Develop systems for: Task decomposition Autonomous navigation & decision making Human-robot interaction (natural language interfaces) Connect AI agents withrobot hardware APIs, sensors, and actuators Work onreal-time constraints, edge deployment, and latency optimization Implementvision + language models (VLMs)for perception-driven reasoning Ensure safety, reliability, and fallback mechanisms in autonomous systems Required Skills & Qualifications 5+ years inAI/ML, Robotics, or Software Engineering Strong programming inPython(C++ is a big plus for robotics) Hands-on experience with: ROS / ROS2 Robotics simulation tools (Gazebo, Isaac Sim, Webots, etc.) Sensor integration (LiDAR, cameras, IMU) Experience with: RAG pipelines & vector databases LLM frameworks(LangChain, LlamaIndex, etc.) Agent-based systems (planning + tool use) Understanding of: SLAM, path planning, and control systems Computer vision (OpenCV, deep learning models) Real-time system constraints Preferred Qualifications Experience withembodied AI / autonomous robots Exposure tomulti-agent robotics systems Experience withedge AI deployment (NVIDIA Jetson, embedded systems) Familiarity withVLMs (Vision-Language Models)and multimodal AI Experience integratingLLMs with physical systems Candidates based in or willing to relocate toGujaratpreferred Soft Skills Strong systems thinking (hardware + software integration) Ability to debug complex real-world systems Ownership mindset and experimentation-driven approach What You’ll Build Robots that canunderstand instructions in natural language Systems thatreason before acting in physical environments AI agents that combinememory (RAG) + perception + action

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