KPIT Technologies

Key Responsibilities

· Define validation strategies, plans, acceptance criteria, and coverage goals for autonomous and AI-enabled functions.

· Analyze system, functional, scenario, safety, and regulatory requirements and translate them into traceable test cases.

· Create, review, maintain, and execute manual and automated test cases across component, subsystem, integration, and vehicle levels.

· Develop reusable test automation frameworks, scripts, utilities, reporting workflows, and continuous validation pipelines.

· Build and execute simulation scenarios using IPG CarMaker, CARLA, and comparable virtual validation environments.

· Perform scenario-based testing across normal, edge, corner, degraded, and failure conditions, including parameter variation and large-scale regression campaigns.

· Validate the end-to-end stack, including sensor inputs, perception, localization, prediction, planning, control, and vehicle or actuator response.

· Evaluate AI model and system behavior for accuracy, robustness, consistency, explainability, performance limitations, and operational-design-domain constraints.

· Analyze logs, metrics, test results, and failures; isolate root causes and work with systems, AI/ML, simulation, software, controls, and safety teams to drive closure.

· Maintain requirements-to-test traceability, evidence, dashboards, defect records, validation reports, and release-readiness recommendations.

· Contribute to audit-ready validation evidence and demonstrate compliance with applicable engineering standards, internal processes, and regulatory expectations.

Required Experience and Qualifications

· Strong domain experience in autonomous driving, ADAS, robotics, intelligent mobility, or a closely related AI-enabled system domain.

· Demonstrated experience in validation and verification of complex, safety-relevant systems.

· Hands-on experience in test design, test-case creation, requirements-based testing, scenario-based testing, and test automation.

· Extensive working experience with simulation platforms, particularly IPG CarMaker and CARLA.

· Experience validating end-to-end autonomous-system behavior rather than isolated algorithms alone.

· Good understanding of the autonomous-driving stack: sensing, perception, sensor fusion, localization, prediction, planning, control, and actuation.

· Experience with result analysis, defect triage, root-cause investigation, coverage assessment, and technical reporting.

· Working knowledge of automotive safety, SOTIF, cybersecurity, homologation, data governance, and AI-related compliance considerations relevant to validation.

· Ability to collaborate across multidisciplinary engineering teams and communicate validation risks, gaps, and evidence clearly.

Preferred Technical Exposure

· Python or another scripting language for test automation, data analysis, orchestration, and report generation.

· Model-in-the-loop, software-in-the-loop, hardware-in-the-loop, vehicle-in-the-loop, and scenario-in-the-loop validation methods.

· OpenSCENARIO, OpenDRIVE, road-network modelling, scenario generation, replay, parameter sweeps, and synthetic-data workflows.

· CI/CD integration, automated regression, distributed simulation, cloud-based execution, and test management tools.

· Quantitative validation metrics for detection, tracking, localization, planning, control, safety, comfort, and system performance.

· Functional safety and safety-of-the-intended-functionality concepts, including hazard-based testing, fault injection, and evidence-based release decisions.

· AI assurance topics such as dataset representativeness, bias and performance analysis, robustness, model limitations, traceability, monitoring, and change impact.

AI Validation,IPG CarMaker,CARLA,AI/ML,autonomous-driving stack,CI/CD integration, OpenSCENARIO, OpenDRIVE,MIL/SIL/HILVIL Validation methods
Autonomous / AI Systems,autonomous driving, ADAS, robotics, intelligent mobility