Sr. Software Engineer(AI & Defence Systems)

Sr. Software Engineer (AI and Defence Systems)
Role Summary-
Location: Noida (Sector 132)
Employment Type: Full-time
Experience : 5-8 years
Industry- Defence and Aerospace
About the Company-
Zoid is a high-tech R&D startup devoted to developing cutting-edge technologies in the Defence and Aerospace sector. We primarily deliver customized solutions to the Indian Armed Forces, leveraging our expertise in AI, Electronics, Unmanned Aerial Vehicles, and Robotics.
Currently funded by the iDEX initiative under the Ministry of Defence, India, we are working on projects of strategic national importance, including:
- AI-based FOD detection software for Naval Air Stations
- Reusable Off-board Missile Decoys for Anti-Ship Missile Defense
ROLE OVERVIEW
We are seeking an experienced Senior Software Engineer to design and lead our software architecture, AI/Computer Vision systems integration, and embedded systems infrastructure. You will be a technical leader who codes, architects, and mentors—driving both strategic system design and hands-on execution. You will take ownership of end-to-end software systems, from hardware abstraction layers through AI pipelines, ensuring performance, reliability, and scalability for defence and aerospace applications.
KEY RESPONSIBILITIES -
Design & Architect Core Software Systems
Define system architecture for project requirements.
Create modular, scalable design patterns that handle real-time sensor inputs and AI inference pipelines
Design hardware abstraction layers for seamless integration with various sensors (cameras, LiDAR, thermal) and edge processors
Establish data flow architecture, APIs, and communication protocols between components
Document architectural decisions, design patterns, and system specifications
2.Production Code Development in C++
Write high-performance, production-grade C++ code for critical system components
Develop code for GPU-accelerated AI inference and image processing
Implement multi-threaded, real-time systems with stringent latency requirements
Conduct performance profiling and optimization (memory, CPU, GPU utilization)
Maintain code quality through testing, code reviews, and documentation
3.Lead AI & Computer Vision Implementation
Own the integration of AI/CV models (detection, tracking, anomaly detection) into production systems
Optimize model inference pipelines for edge deployment on resource-constrained devices
Implement real-time processing frameworks handling multi-camera feeds and sensor fusion
Benchmark and optimize performance (latency, throughput, memory footprint)
Work on model quantization, pruning, and optimization for efficient edge execution
4. Hardware & Sensor Integration
Lead integration efforts with hardware teams: cameras, compute modules, networking equipment, sensors
Define hardware requirements and validate hardware selections
Implement device drivers, firmware interfaces, and hardware communication protocols
Ensure systems remain reliable in long-term industrial/defence deployments.
Interface with GNSS receivers, inertial measurement units (IMUs), industrial cameras, thermal/IR cameras, LIDAR, rangefinders, communication radios, gimbal systems, and other peripherals.
Contribute to open-source drivers, configure kernel modules, and write integration layers.
For specialized hardware (e.g., Basler/FLIR industrial cameras, Veronte autopilots, military-grade radios): work with manufacturer SDKs, understand vendor-specific APIs and protocols.
Communicate over serial protocols (UART, SPI, I2C, RS-232, RS-422) .
5.Linux Systems Software
Set up and optimize Linux kernel configurations for real-time performance
Provision, configure, and harden Linux (Ubuntu) OS images for field-deployed systems: minimal attack surface, systemd service management, user/permission lockdown.
Implement process management: watchdog timers, heartbeat monitoring, automatic service restart, graceful shutdown sequencing, zombie process management.
Write robust Bash scripts for Ubuntu command-line automation
Manage system-level drivers, device tree configurations, and boot processes
Implement system monitoring, logging, and telemetry frameworks
Handle cross-compilation, build systems (CMake, Yocto), and deployment pipelines
6.Networking & Infrastructure Development
Design and implement network communication layers (Ethernet, CAN, MQTT, gRPC)
Set up edge computing infrastructure and distributed system communication
Implement secure communication protocols and data transmission standards
Manage system interconnectivity
Build TCP/UDP socket communication, RTSP video streaming pipelines, and mesh networking for multi-node systems.
7.Technical Planning & Execution
Create technical roadmaps aligned with product goals (6-12 month outlook)
Break down complex architectural work into executable sprints and milestones
Identify technical risks, performance bottlenecks, and scalability challenges early
Drive solutions and proof-of-concepts for new technical requirements
Coordinate with systems engineers on end-to-end testing and validation
Support field testing and customer deployment efforts with technical expertise
REQUIRED QUALIFICATIONS
5-8 years of software development experience in complex, real-time systems
Expert-level proficiency in C++ ; deep understanding of memory management, concurrency,multi-threading, and performance optimization
Strong hands-on experience optimizing AI inference on GPUs
Proven background in AI/Computer Vision (model deployment, PyTorch/TensorFlow, OpenCV)
Deep experience with Linux kernel and linux based OS, system programming, device drivers, and embedded systems
Solid knowledge of networking protocols, hardware integration, and sensor interfaces
Experience with technical documentation and architectural design patterns
Proven experience designing architectures for real-time or mission-critical systems: module decomposition, IPC, state machines, data flow, deployment topology
Experience building multi-threaded and multi-process systems on multi-core and/or multi-GPU hardware.
Produce documentation to IEEE/ISO/IEC 12207 and IEEE 29148 (prior experience not mandatory; learn within the first few months)
Demonstrated problem-solving and systems-level thinking
Leadership experience (formal team lead)
Strong communication skills; ability to explain complex technical concepts
DESIRABLE QUALIFICATIONS
Experience with defence or aerospace software systems and constraints
Knowledge of distributed systems, edge computing, and system scalability patterns
Experience with CI/CD pipelines, automated testing, and DevOps practices
Ability to produce defence-grade engineering documentation to IEEE 12207 or demonstrated aptitude to learn.
Implement pub/sub middleware (DDS) for real-time communication in distributed defence systems, including domain partitioning, QoS policy configuration, and topic architecture.
Experience deploying ML inference pipelines on edge hardware (Jetson, NUC) or server hardware (multi-GPU, TensorRT, ONNX Runtime, CUDA).
DDS middleware implementation including QoS configuration and domain architecture.
Hardware integration experience: sensor bring-up, serial protocols (UART, SPI, I2C, RS-422), industrial camera SDKs (Basler, FLIR, Allied Vision).
Familiarity with defence software standards (DO-178C, MIL-STD-498, STANAG 4586).
CODE- SOFTTECH

Work arrangement
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