Job Description

• Develop and implement software modules for AI-based surveillance systems in accordance with IEEE software engineering standards and internal development guidelines.
• Implement application-level components supporting video ingestion, data processing, and analytics pipelines for surveillance use cases.
• Support integration of AI/ML inference modules (e.g. object detection or tracking outputs) into application software.
• Prepare and maintain software design documentation, including architecture descriptions, module specifications, and interface definitions.
• Develop and execute software test plans, including unit testing, black-box testing, and white-box testing, to verify functional correctness and performance.
• Support software validation and verification (V&V) activities, including defect analysis, bug fixing, and regression testing.
• Collaborate with system engineers and solution architects to ensure software modules integrate correctly with system-level designs.
• Maintain version control, documentation updates, and test records to support audit and traceability requirements.
• Support ongoing software maintenance and enhancement activities across multiple project phases.

Requirements

Core Technical Skills

• Proficiency in C++ and/or Python for software module development.
• Working knowledge of software engineering best practices, including modular design, version control, and coding standards.
• Experience developing software in Linux-based environments.

AI / Surveillance System Context

• Familiarity with video processing pipelines, including frame handling, data streaming, or sensor data integration.
• Basic understanding of AI-based computer vision systems, such as object detection, tracking, or event analysis (integration-level, not model research).
• Experience integrating software modules with AI inference outputs.

Software Testing & Quality

• Experience in unit testing, black-box testing, and white-box testing.
• Knowledge of software verification and validation (V&V) processes.
• Ability to document test procedures, test results, and defect reports.

Development Tools & Frameworks

• Experience using Git or equivalent version control systems.
• Familiarity with build systems and development tools (e.g. CMake, GCC, or equivalent).
• Exposure to containerized or modular deployment environments (e.g. Docker) is an advantage.

Documentation & Standards

• Ability to produce and maintain software design and test documentation in line with IEEE software engineering standards.
• Familiarity with structured documentation practices to support audits and traceability.

Collaboration & Work Practices

• Ability to work within a multi-disciplinary engineering team, including system engineers and solution architects. Comfortable working in a project-based, structured development environment with defined requirements and deliverables.