AI Engineer with less than a year in LLM Debugging & Backend Systems
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Software Engineer focused on backend systems, automation, and AI evaluation workflows. Experience building production LLM debugging and evaluation pipelines, event-driven services, REST APIs, and microservice-based systems using Python, TypeScript, Docker, Kubernetes, and RabbitMQ. Strong interest in quality engineering, regression detection, and reliable system behavior across API-driven and AI-assisted workflows.
AMC Engineering College
Bachelor of Engineering · Computer Science and Engineering
N/A – June 30, 2026
Samora AI (YC W26)
Prompt Engineering Intern
January 1, 2026 – March 1, 2026
India
Airlearn (Unacademy)
Operations Intern
August 1, 2025 – August 1, 2025
Bengaluru, Karnataka, India
ATRA - Autonomous Trading System
February 1, 2026 – June 1, 2026
Built an event-driven backend system with REST APIs for simulation and evaluation workflows. Implemented execution logic with realistic constraints such as latency, slippage, and partial fills to test system behavior. Designed modular workflow separation for simulation, evaluation, and output layers to support repeatable validation.
DeedLens
November 1, 2025 – January 1, 2026
Built a Retrieval-Augmented Generation pipeline using embeddings and FAISS for semantic search over unstructured documents. Developed REST APIs for querying and generating context-aware responses. Designed chunking, embedding, and retrieval workflows to improve response relevance and accuracy.
Agentic DevOps System
March 1, 2025 – December 1, 2025
Built a multi-agent system coordinating through message queues for event-driven task execution. Integrated a vector database to retrieve historical logs and context for better debugging and decision-making. Developed microservices with Docker and Kubernetes for scalable deployment and orchestration. Added workflow automation and structured event handling across the pipeline.
Winner, ThinkUp Ideathon
Unknown
January 1, 2025 – Present
2nd Place, Algo Arena Hackathon
Unknown
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity (DevOps, Document Intelligence, Trading System) and engagement in hackathons suggest a curious and adaptable individual. The target role of AI Engineer aligns well with their demonstrated interest and project work in LLMs, RAG, and agentic systems. Their skills breadth, including Python, TypeScript, Docker, Kubernetes, and various AI/ML tools, indicates a willingness to learn and apply diverse technologies. However, the limited professional experience means cultural fit is primarily inferred from project work and academic achievements.
Soft Skills & Operational Fit
The candidate demonstrates initiative through personal projects and hackathon achievements. Their internship experience at Samora AI shows collaboration with backend engineers and a focus on improving system reliability, indicating a team-oriented approach and attention to quality. The Airlearn internship, though brief, suggests an ability to translate product requirements into technical workflows. However, the overall experience is limited, and deeper insights into stress handling, complex problem-solving under pressure, or leadership are not explicitly available.