Subhajeet Roy

AI Engineer with 3.5+ years designing, building, and deploying production-grade GenAI automations, agentic AI workflows, and RAG systems from concept to production. Hands-on experience architecting AI Agents from scratch using LangGraph and LlamaIndex with Tool Use, multi-turn memory, and autonomous planning loops.

Strong

Python and REST API engineering background with software practices (testing, linting, modular design), complemented by working knowledge of JavaScript and SQL. Proven ability to balance low-code and pro-code approaches, integrate LLMs with APIs and data sources, and ship reusable, secure, observable AI components into production via CI/CD, containerization, and MLflow.

AI Integration Contributor | QA Automation Analyst at Saks Global India (2022-01 – Present)

• Designed and shipped LLM-based automation workflows to production – prompt-driven test generation and regression analysis – applying agentic AI tooling to reshape manual analytical work into scalable automations.
• Built REST API automation suites enforcing schema contracts; directly applied to LLM output validation, structured-output testing, and RAG evaluation, ensuring AI components operated safely within business constraints.
• Architected Jenkins CI/CD pipelines with MLOps-style regression validation and continuous deployment for AI systems, balancing low-code and pro-code approaches to maximize speed without compromising reliability.
• Acted as technical liaison between data and engineering teams, refactoring experimental models and prompts into production-grade, reusable, and observable AI components.
• Conducted EDA on production logs and communicated specialized technical findings to non-technical stakeholders to drive Agile prioritization.

B.Tech in Computer Science Engineering – Presidency University (2018-01 – 2021-01)

Diploma in Computer Science Engineering – Ramaiah Polytechnic (2015-01 – 2018-01)