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System engineer - Mobile robotic

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Onsite

System engineer - Mobile robotic

Prominent Management Solutions

System engineer - Mobile robotic

Skills

PythonLinux

1 month ago

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Important information


Contract type:

Permanent

Location:

Gurugram, Haryana, India

Work mode:

Onsite

Published on:

24 September 2026

What they need


Role Summary

We are seeking a Systems Engineer to support deployment, commissioning, troubleshooting, and lifecycle support for Autonomous Mobile Robots (AMRs) and robotic automation systems at customer sites.

The engineer will be responsible for diagnosing and resolving complex issues spanning software, embedded systems, networking, controls, electrical systems, and mechanical integration. The role requires strong analytical thinking, structured problem-solving, and the ability to work across multiple engineering disciplines.

Key Responsibilities

  • Commission and validate robotic systems at customer sites.
  • Diagnose and resolve hardware, software, electrical, and networking issues.
  • Perform root cause analysis for field failures and recommend corrective actions.
  • Support installation, configuration, calibration, and acceptance testing of robotic systems.
  • Debug ROS-based software stacks and system-level integrations.
  • Analyze system logs, diagnostics, and performance data to identify failures.
  • Work closely with Product Engineering, Controls, Mechanical, Electronics, and Software teams to resolve complex technical issues.
  • Document field observations, investigation reports, and corrective actions.
  • Develop and execute validation procedures for new features and fixes.
  • Support customers remotely and onsite during commissioning and production operations.
  • Identify recurring field issues and provide feedback to product development teams to improve product reliability.

Required Technical Skills

Robotics & Automation

  • Robotics fundamentals
  • Mobile robot kinematics
  • Localization and Navigation concepts
  • SLAM fundamentals
  • Path planning concepts
  • Motion control fundamentals
  • Sensor integration

Software

  • ROS / ROS2
  • Linux (Ubuntu)
  • C++ and/or Python
  • Shell scripting
  • Git

Embedded & Controls

  • Embedded systems fundamentals
  • PLC interaction
  • CAN, RS485, UART, Modbus communication
  • Motor controllers and drive systems
  • Sensor interfaces

Networking

  • TCP/IP fundamentals
  • Ethernet networking
  • IP configuration
  • Routing and switching basics
  • Network diagnostics using common tools

Diagnostics & Validation

  • Log analysis
  • System debugging
  • Root cause analysis
  • Failure reproduction
  • Functional testing
  • Integration testing

Desired Knowledge

  • LiDAR, Camera, IMU, Encoder integration
  • Safety scanners and industrial safety systems
  • Industrial automation
  • Warehouse automation
  • AGV/AMR systems
  • Industrial communication protocols
  • Field commissioning experience

Core Competencies

  • Strong analytical and logical reasoning
  • Systems thinking
  • Structured problem-solving
  • Hypothesis-driven debugging
  • Root cause analysis
  • Attention to detail
  • Ability to work under time-critical situations
  • Cross-functional collaboration
  • Technical documentation and reporting
  • Customer-facing communication

Preferred Qualifications

  • Bachelor's or Master's degree in Robotics, Mechatronics, Electronics, Electrical Engineering, Computer Science, Instrumentation, or related discipline.
  • 2-6 years of experience in robotics, industrial automation, embedded systems, or technical support.
  • Experience with AMRs, AGVs, autonomous systems, or industrial automation products is preferred.

What Success Looks Like

The successful candidate will be able to:

  • Independently diagnose and resolve complex system-level issues.
  • Identify the root cause of field failures rather than treating symptoms.
  • Work effectively across software, hardware, controls, and mechanical domains.
  • Communicate technical findings clearly to both customers and internal engineering teams.
  • Contribute to continuous improvement by feeding field learnings back into product development.

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