AI SDET

About Us 

We’re Hitachi Vantara, a global infrastructure business. Our people are the force of meaningful progress. We enable the incredible with data – from taking theme park fans on magical rides, conserving natural resources, protecting rainforests to saving lives. We empower businesses to automate, optimize, and advance innovation. Together, we create a sustainable future for all. 

Imagine the sheer breadth of talent it takes to inspire the future. We don’t expect you to ‘fit’ every requirement – your life experience, character, perspective, and passion for achieving great things in the world are equally important to us. 

Role Overview 

Hitachi Vantara is seeking an AI SDET to join our Global Quality Assurance team. In this role, you will design and execute test strategies for AI‑driven systems, including LLM‑powered features, machine learning components, and intelligent automation workflows. 

You will collaborate closely with product teams, data scientists, ML engineers, and platform teams to validate AI behavior across the full lifecycle—from data ingestion and model inference to system integration and user‑facing functionality. This includes evaluating model outputs, ensuring reliability and safety, validating data pipelines, and building tooling that supports predictable, high‑quality AI experiences. 

This role is ideal for an engineer who enjoys blending software testing, system integration, and applied AI behavior analysis. 

Experience: 7–10+ Years 
Job Location: Kolkata, India preferred 

Key Responsibilities 

• AI System Validation: Test and validate AI/ML features across internal models, embedded AI components, and integrated AI services. 

• Model Behavior Evaluation: Assess model inference quality, prompt/response behavior, performance, safety, and robustness across diverse scenarios. 

• Data Pipeline & Schema Verification: Validate data contracts, feature schemas, and payload structures used by AI models and downstream systems. 

• End‑to‑End Workflow Testing: Ensure AI‑driven workflows function reliably across internal components, orchestration layers, and user‑facing applications. 

• Tooling & Automation: Build tools to simulate AI behavior, automate evaluation workflows, generate test datasets, and support continuous validation. 

• AI Quality & Reliability: Identify edge cases, failure modes, drift indicators, and quality gaps in AI‑powered features. 

• Security & Responsible AI Checks: Validate compliance with security, privacy, fairness, and responsible AI guidelines. 

• Cross‑Functional Collaboration: Work with product, engineering, and data science teams to troubleshoot issues, validate fixes, and improve AI feature readiness. 

• Documentation: Produce clear documentation for AI test plans, expected behaviors, evaluation criteria, and validation procedures. 

• Continuous Improvement: Propose enhancements to improve AI reliability, observability, and test coverage across the lifecycle. 

Required Skills 

• 7–10+ years of experience in software testing or SDET roles, with 2+ years focused on AI/ML systems. 

• Strong proficiency in Python for test development, data validation, and evaluation tooling. 

• Strong foundational knowledge of storage technologies, such as block storage, object storage (S3‑compatible systems), NFS, or distributed file systems. 

• Knowledge of Hitachi products such as VSP 360 ,Ops Center will be an added advantage. 

• Experience with AI/ML frameworks or platforms such as PyTorch, TensorFlow, Scikit‑learn, Hugging Face, Azure AI, AWS AI/ML, or Google Vertex AI. 

• Understanding of AI/ML concepts including:  

• model inference behavior 

• evaluation metrics 

• prompt/response quality 

• drift, bias, and fairness considerations 

• Experience testing LLM‑based systems or ML‑powered features. 

• Familiarity with MLOps tools and workflows (MLflow, Kubeflow, SageMaker, Vertex AI, etc.). 

• Strong understanding of QA methodologies, SDLC, and agile practices. 

• Experience with Linux/UNIX environments and containerized workflows (Docker). 

• Excellent communication skills and ability to collaborate across global teams. 

Preferred Qualifications (AI‑Focused Certifications) 

• Microsoft Certified: Azure AI Engineer Associate 

• AWS Certified Machine Learning – Specialty 

• Google Professional Machine Learning Engineer 

• NVIDIA Deep Learning Institute Certifications (LLMs, generative AI, computer vision) 

• TensorFlow Developer Certificate 

• Hugging Face NLP/LLM Certifications 

• ISTQB Certified Tester – AI Testing 

• Certified Kubernetes Administrator (CKA) or CKAD 

#LI SP7