Evaluation Engineer, Intern

About the Role

Aura Cloud is seeking curious, analytical, and AI-oriented Evaluation Engineers to evaluate features across their AI-embedded banking platform. This role involves translating requirements into evaluation scenarios, defining correctness, exercising the platform, and analyzing results to establish functionality, accuracy, and reliability, utilizing AI tools throughout the process.

Key Responsibilities

• Build AI-based frameworks for evaluation of AI-generated code.
• Use AI tools to design use cases, evaluation scenarios, and workflows for validating platform features.
• Understand platform requirements and evaluate whether new features meet them.
• Run evaluation scenarios, compare actual against expected outcomes, and identify gaps, inconsistencies, and failure modes.
• Utilize AI tools to generate scenarios and data, and to automate and improve coverage and speed.
• Diagnose failures to the point of knowing what broke and why; classify failure modes, document them, and drive issues to closure.
• Build the harnesses and pipelines that operate repeatably and at scale for evaluation automation.
• Maintain clear records of use cases, evaluation criteria, results, observations, and issues.
• Work closely with Engineering through the feature lifecycle.
• Explore new AI tools, evaluation techniques, and methodologies to strengthen coverage and effectiveness.

Requirements & Tech Stack

• B.Tech / B.E. / B.Sc. (2026 & 2025 batches) in Computer Science, Information Technology, or a related discipline.
• Working knowledge of generative AI tools, Large Language Models, backed by project work on GitHub.
• Sound grasp of software development concepts, programming fundamentals, and evaluation principles.
• Working ability in at least one language — Python, JavaScript — to call an API, parse the response, and assert something about it.
• Strong analytical and logical reasoning skills.
• The instinct to ask "how would I know if this were wrong?"
• Clear written and verbal communication, with attention to detail and a structured approach to documentation.
• Willingness to learn quickly and work in a fast-paced product.

Preferred / Good-to-Have Skills:

• Using AI tools to design evaluation scenarios, generate data, and assess software output.
• Automating repeatable checks, debugging, and working with Git.
• REST APIs, JSON, SQL, and database fundamentals.
• Reasoning about coverage: functional, regression, and edge-case scenarios.

Key Competencies

• Translating requirements into evaluation scenarios that catch failures.
• Analytical thinking and structured problem-solving.
• Precision, and a bias toward proving correctness.
• Ownership, adaptability, and speed of learning.
• Clear communication and cross-functional collaboration.