Senior AI / Embedded Software Engineer

· Company: Cyber Joar AI Pvt Ltd · Location: Gurugram · Job Type: Full-time (1-3 Yrs Exp)

We build AI-driven, hardware-integrated platforms that empower defense, security, and intelligence organizations to collect, process, and analyze vast amounts of data in real time, often at the tactical edge. We are seeking a highly skilled Senior AI and Embedded Software Engineer to bridge the gap between complex artificial intelligence models and low-power embedded hardware.

The Role:

As a Senior AI/Embedded Software Engineer, you will play a critical role in designing and deploying intelligent firmware and software that runs directly on edge devices, drones, and proprietary hardware systems used for OSINT collection and analysis. You will optimize machine learning (ML) algorithms to run efficiently on resource-constrained embedded systems and ensure secure, real-time data transmission back to our core OSINT analytical platforms.

You will work at the intersection of cybersecurity, hardware engineering, and data science, ensuring our intelligence-gathering devices are smart, secure, and highly efficient.

Key Responsibilities:

• Embedded AI Development: Design, develop, and deploy C/C++ firmware and embedded software for microcontrollers and embedded Linux environments.
• Edge AI Optimization: Port and optimize AI/ML models (e.g., TinyML, computer vision, NLP, or signal processing algorithms) to run on resource-constrained hardware (ARM Cortex, edge TPUs, or FPGAs) for real-time, on-device intelligence.
• OSINT Integration: Develop software pipelines that allow embedded devices to securely collect, filter, and transmit relevant unstructured data (signals, localized web data, telemetry) to our centralized OSINT platforms.
• Hardware/Software Co-design: Collaborate closely with hardware engineers during board bring-up, debugging, and testing of new tactical intelligence devices.
• System Security & Hardening: Implement robust hardware security protocols (Secure Boot, cryptography, TEE) to ensure that embedded intelligence devices are resilient against physical tampering and cyber-attacks.
• Debugging & Troubleshooting: Perform deep system-level debugging using oscilloscopes, logic analyzers, JTAG, and GDB to resolve cross-layer issues between hardware, firmware, and the OS.
• Documentation & Leadership: Mentor junior engineers, conduct code reviews, and maintain clear technical documentation for embedded software architecture and APIs.

Minimum Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field.
• Experience: 5+ years of hands-on experience in embedded software/firmware engineering.
• Programming: Strong proficiency in C and C++ for embedded systems; proficiency in Python for scripting, ML integration, and automation.
• OS Knowledge: Deep understanding of Embedded Linux (Yocto/Buildroot) and Real-Time Operating Systems (RTOS).
• Hardware Interfacing: Experience with low-level communication protocols (I2C, SPI, UART, GPIO) and debugging tools.
• AI/ML Exposure: Practical experience deploying machine learning models to the edge (e.g., using TensorFlow Lite for Microcontrollers, ONNX, or NVIDIA Jetson platforms).

Preferred Qualifications (Standout Skills):

• Intelligence Background: Prior experience or strong understanding of Open Source Intelligence (OSINT), SIGINT, or threat intelligence data pipelines.
• Security Expertise: Experience with embedded security, penetration testing, or reverse engineering (CEH or similar certifications are a plus).
• IoT/Networking: Familiarity with secure IoT communication protocols (MQTT, CoAP) and edge-to-cloud architecture.
• Clearance: Active security clearance or the ability to obtain one is highly desirable due to the nature of our client base.

How to Apply: Please submit your resume to - [ [email protected] ] with the subject line “Senior AI / Embedded Software Engineer” ., along with a brief cover letter highlighting a specific project where you successfully deployed software (preferably AI/ML) onto an embedded system. Links to GitHub repositories or open-source contributions are highly encouraged.