Scenario Creation - Maintenance Engineer

Experience:
3-8 Years
Job Summary:
We are seeking highly analytical engineers to support the creation, maintenance, and optimization of testing scenarios for autonomous driving systems. The role involves transforming real-world operational data and logged system events into structured, reproducible test scenarios that improve validation coverage and system reliability. The ideal candidate should possess strong systems thinking, diagnostic troubleshooting capabilities, and the ability to work across complex software architectures and simulation environments.
Key Responsibilities
Analyze system logs, telemetry data, and operational events to generate and maintain test scenarios.
Design scalable test configurations that can be applied across large automated testing pipelines.
Understand and model interactions between software modules, environmental conditions, and simulation parameters.
Convert complex system behaviors into repeatable validation scenarios and test datasets.
Perform diagnostic analysis and reverse engineering of system behavior to identify edge cases and failure patterns.
Collaborate with testing, simulation, software engineering, and data teams to improve scenario quality and coverage.
Develop rule-based and parameterized scenario generation frameworks.
Ensure generated scenarios are robust, scalable, and representative of real-world operating conditions.

Candidates from the following domains are highly preferred:
QA Automation Engineering
Data Analytics
Technical Support Engineering (L3/L4)
Systems Integration
Software Validation & Testing
Simulation Engineering
Test Automation Engineering
Autonomous Vehicle / ADAS Validation
Game Simulation & Scenario Design
Educational Qualification:
Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Physics, Video Game Design, or related technical discipline.
Candidates with a 3-year degree should have a relevant Master's degree or significant domain experience.

Required Skills
Systems Architecture & Modular Thinking
Strong understanding of complex software architectures, state machines, and system interactions.
Ability to analyze how different software components, environmental physics, and simulator configurations influence overall system behavior.
Parametric Design & Spatial Logic
Knowledge of Boolean logic, geometric constraints, and time-based validation rules.
Experience working with structured configuration languages such as JSON or XML.
Ability to build reusable, scalable test configurations and validation rules.
Experience working with automated testing pipelines and large-scale data processing environments.
Strong systems-level thinking and automation mindset.
Robustness & Boundary Value Analysis
Strong understanding of edge cases, tolerances, and validation methodologies.
Ability to design scenarios that remain resilient under variable system conditions.
Diagnostic & Analytical Skills

Role Title
Scenario Creation & Maintenance Engineer - Log Based Test Generation (Diagnostic Focused)
Experience
3-8 Years
Location
India
Job Summary
We are seeking highly analytical engineers to support the creation, maintenance, and optimization of testing scenarios for autonomous driving systems. The role involves transforming real-world operational data and logged system events into structured, reproducible test scenarios that improve validation coverage and system reliability. The ideal candidate should possess strong systems thinking, diagnostic troubleshooting capabilities, and the ability to work across complex software architectures and simulation environments.
Key Responsibilities
Analyze system logs, telemetry data, and operational events to generate and maintain test scenarios.
Design scalable test configurations that can be applied across large automated testing pipelines.
Understand and model interactions between software modules, environmental conditions, and simulation parameters.
Convert complex system behaviors into repeatable validation scenarios and test datasets.
Perform diagnostic analysis and reverse engineering of system behavior to identify edge cases and failure patterns.
Collaborate with testing, simulation, software engineering, and data teams to improve scenario quality and coverage.
Develop rule-based and parameterized scenario generation frameworks.
Ensure generated scenarios are robust, scalable, and representative of real-world operating conditions.