Vatsal Saglani

Bengaluru · Quinnox, Jul 2024 – Feb 2026 · Qyrus India, Mar 2026 – present (one continuous role)

• Built and maintain a shared Python agent SDK and execution harness adopted across internal AI applications, standardizing model calls, tool execution, retries and guardrails, with token, latency, error and trace telemetry.
• Led Device Farm AI Sessions: users state a testing objective in plain language and agents operate real Android and iOS devices to produce reusable tests, with live guidance, parallel sessions, reruns and step-by-step evidence.
• Architected execution and reporting on AWS AgentCore and ECS, separating live session streams from durable run history and artifacts, with CI/CD integration and enterprise deployment support.
• Developed an agent-driven browser automation framework with streaming execution, accessibility checks and network traces; prototyped multi-agent workflows coordinating isolated web and mobile agents through shared task context.
• Architected a hybrid agent memory system combining graph relationships, semantic retrieval, metadata and object storage, with queue-driven ingestion decoupled from retrieval for multimodal context and long-running workflows.
• Built LLM and RAG evaluation and led LLM-as-judge integration for API testing; designing evaluation of full agent trajectories and persona scenarios with deterministic checks plus LLM judges, implementation ongoing.
• Implemented code-change impact analysis linking Python changes to business requirements and affected tests, surfacing misalignment, thin evidence and coverage gaps.
• Developed an IDE extension for code search and API test generation (assertions and test data), and skills for API testing and MCP-backed web testing in AI coding assistants.
• Prototyping a compact vision-language computer-use model that predicts actions and coordinates from screenshots and objectives, including a direct spatial prediction head and training and evaluation scaffolding (research, not production).
• Set technical direction, mentor engineers and plan delivery with product stakeholders; partner with client-facing teams on responsible AI, safety and compliance documentation.
• Participate in Forrester and Gartner analyst briefings, explaining QyrusAIAI's AI capabilities and demonstrating agent-driven testing workflows.

Bengaluru

• Led development of the Generative AI Software Testing Kit (STK), a Python package that let traditional QA teams use AI in their existing workflows.
• Designed a cloud API-testing agent on LLMs with robust fallback strategies, and copilot bots for web, mobile, API and desktop testing.
• Trained transformer models from scratch for text classification and NER, and a decoder-only recommender that suggests the next step while authoring tests.
• Fine-tuned DETR, Detectron2 and YOLO for UI element detection, and fine-tuned Mistral and Llama for custom vision and text tasks.
• Built a self-serve RAG system with tool integration (bring your own actions) and a distributed chatbot-testing service on Kafka, DynamoDB and Redis.
• Led a four-person team shipping a desktop-app testing and data comparison service on SQS and Lambda.

Bengaluru

• Shipped text classification models with scikit-learn, FastText and Gensim, and transformer-based NER.
• Designed a text augmentation process that injects realistic errors to harden models against noisy input.
• Built a unified async backend (FastAPI, Flask, aiohttp) serving predictions from a fleet of models.

• Wrote OpenCV algorithms to isolate diseased regions of crops and a meta-learning classifier for disease type, then integrated both into a deployed pipeline.

Network traffic analysis across switches to optimise cluster efficiency, cutting cost and energy use.

GPA 8.48/10. VIT Best Project Award, 2019. Published four papers as an undergraduate.