Rajesh Kumar Sahoo

About Rajesh Kumar Sahoo

With over 13 years of experience in automation, automotive systems, and model validation, I specialize in bridging the gap between classical automotive validation workflows and modern AI-driven test generation frameworks.My recent work focuses on leveraging Large Language Models (LLMs) and prompt engineering to automate functional test-case generation for complex automotive systems — including ECU-level signal validation, requirement traceability, and end-to-end test automation pipelines.Throughout my career, I’ve contributed to projects that enhance testing efficiency, standardize validation processes, and improve software quality in compliance with automotive standards such as ISO 26262 and ASPICE.Core Expertise: • Automotive software validation & model-based testing (MIL/SIL/HIL) • Test automation frameworks (Python, CAPL, CANoe, Robot Framework) • Requirement analysis & test design from system specifications • LLM prompt engineering for test-case generation & dataset curation • End-to-end validation strategy and test coverage improvementCurrently: Building intelligent test-automation systems that use LLMs to parse system-level requirements and generate structured, traceable test cases, enabling faster, smarter validation for next-generation vehicles.

Experience

1. Staff Engineer

   Stellantis

   Jul 2022 — Present · Bengaluru, IN

   AI-Driven Functional Test-Case Generation for Automotive ECUsDeveloped an LLM-based framework to automatically generate functional test cases from system-level requirements. Integrated Azure OpenAI (GPT-5) with Python pipelines for requirement parsing and signal mapping, achieving 40–50% reduction in manual effort and improved traceability across ECU test coverage.2. Model-Based Validation Automation FrameworkBuilt a Python–CAPL–CANoe integrated framework for automated model validation and ECU-level testing. Automated requirement-to-test linking, signal stimulation, and response validation, increasing regression test throughput by 30% and ensuring reusable, standardized test components.

Skills

• Testing
• Vector Canalyzer
• Test Automation
• Team Management
• Ni Teststand
• Ni Labview
• Linux
• Canoe