Headline

Associate AI Engineer | LLM Evaluation & Agentic AI Systems | AI Research Team @ Centific

About

I engineer and evaluate applied AI systems built around LLMs, multimodal models, and agentic workflows, with a focus on reliability and measurable performance. As an Associate AI Engineer at Centific, my work has included LLM and RAG evaluation, multimodal quality assurance, model fine-tuning, an environment for reinforcement learning with verifiable rewards, and AI microservices deployed on Azure. Across these areas, I enjoy turning ambiguous problems into systems and workflows that can be tested, measured, and improved against real-world data, failure cases, and changing requirements. I’m interested in connecting with people building reliable LLM applications, agentic systems, and applied AI products.

Location

Chennai

AI stack

claude code

claude

codex

hugging face

langgraph

mcp

Work experience

Associate AI Engineer | AI Research at Centific, Aug 2025 - Present · 1 yr 1 mo, • Built LLM evaluation infrastructure: an LLM-as-judge framework for model-written code, dimensional rubrics for judging AI agents on finance work, batch model serving on vLLM, and public benchmark runs through Inspect Evals. • Built the screening stage of an agentic video-annotation quality system: two-pass VLM frame analysis, an async orchestrator that fans specialist agents across annotations, and tooling that scores agent findings against human-reviewer actions. • First-authored a paper at ACM AI-SQE 2026 (co-located with ICSE 2026) on enterprise code evaluation, and co-authored an ICML 2026 position paper on quality assurance in annotation pipelines.

Associate Application Engineer - Intern at Centific, Oct 2024 - Jul 2025 · 10 mos, • Developed and optimized backend APIs using Python, Flask, and PostgreSQL, ensuring seamless data integration with frontend systems and improving system reliability. • Designed and implemented scalable backend systems leveraging distributed task queues (Celery, Redis) to enable concurrent executions and improve overall system performance. • Deployed AI services on Azure Kubernetes Service (AKS), containerizing models and integrating them into production pipelines with strong emphasis on CI/CD and testing.

AI/ML Intern at LLMate, May 2023 - Jul 2023 · 3 mos, Bengaluru, Karnataka, India, • Gained valuable experience as an AI/ML Intern for 2 months in a hybrid environment, successfully integrating AI into web and mobile applications across two projects. • Developed a web app, AI Tutor, which functioned as a chatbot to answer student queries based on NCERT science books, aiding CBSE board exam preparation; additionally built a WhatsApp bot, Google Calendar Scheduler, which streamlined event scheduling by directly syncing meetings to Google Calendar, reducing user clicks. • Enhanced teamwork skills, embraced new concepts, and witnessed significant personal growth.

Education

Bachelor of Technology - BTech, Computer Science and Engineering, BML Munjal University

Public links

github: https://github.com/that-rookie-parth