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AI Engineer with 1+ years in Data Science, ML & Backend Development
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Highly motivated and results-driven individual with a foundational background in Data Science, ML Engineering, and Backend Development. Demonstrated ability to architect production-grade microservices, develop AI-powered computer vision pipelines, and conduct end-to-end data analysis. Skilled in FastAPI, PostgreSQL, Docker, and various ML/AI libraries, with a strong focus on building scalable and secure applications.
Indian Institute of Information Technology, Senapati, Manipur
B.Tech · Electronics and Communication Engineering, Specialization in VLSI Engineering
August 1, 2022 – June 30, 2026
PSS Automate Private Limited
Data Science & ML Engineer Intern
June 1, 2025 – Present
Hyderābād, Telangana, India
Arthgrow Solutions Pvt Ltd (Snap Funds)
Data Science & Software Developer Intern
January 1, 2025 – June 1, 2025
India
Centre for Development of Advanced Computing (CDAC Noida)
Cybersecurity Intern
March 1, 2024 – August 1, 2024
Noida, Uttar Pradesh, India
Microservices-Based Appointment Management Platform
January 1, 2026 – Present
Designed and deployed a scalable FastAPI microservices architecture comprising 5 independent, loosely-coupled services with REST-based inter-service communication for high maintainability. Enforced enterprise-grade security through JWT authentication, RBAC, and multi-tenant data isolation ensuring secure, role-specific access control backed by PostgreSQL and Alembic migrations. Delivered fully functional appointment scheduling, invoicing, and payment APIs, containerized via Docker, validated with PyTest, and documented through Swagger/OpenAPI for seamless developer onboarding.
CFU Detection & Counting Service
January 1, 2026 – Present
Engineered a distributed FastAPI backend with Celery workers, Redis task queue, and MinIO S3 storage enabling high-throughput asynchronous colony detection on TFA agar plate images at scale. Secured and optimized the pipeline with JWT authentication and OpenCV adaptive thresholding delivering auditable, lab-accurate CFU counting results backed by PostgreSQL and Alembic-managed migrations. Shipped production-ready job submission, batch processing, and annotated image APIs containerized via Docker Compose, validated against real plate images, and documented through Swagger/OpenAPI for rapid integration.
Deep RAG Agent
January 1, 2026 – Present
Engineered an Agentic RAG System leveraging LangGraph orchestration and Groq's LLaMA 3.3-70B to autonomously retrieve, evaluate, and synthesize answers from a ChromaDB vector knowledge base. Designed a Self-Healing Query Pipeline with intelligent document relevance grading and automatic query rewriting ensuring high-accuracy responses even when initial retrieval fails. Deployed a Cost-Free Production-Ready AI Stack using HuggingFace embeddings, ChromaDB, and Groq API, demonstrating ability to build powerful LLM applications without expensive infrastructure.
View ProjectRV321 Base ISA processor
Maven Silicon
January 1, 2026 – Present
Intership completion certificate
Centre For Development of Advanced Computing
January 1, 2026 – Present
Data visualisation: Empowering Business with Effective Insights
TATA
January 1, 2026 – Present
Data Analytics and visualization job Simulation
ACCENTURE
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from microservices platforms to computer vision and advanced RAG systems, demonstrates a broad technical curiosity and adaptability. The involvement in campus ambassador roles and certifications from various organizations suggests a proactive learning attitude and engagement beyond academic requirements. The blend of backend, data science, and AI roles indicates a versatile profile suitable for cross-functional collaboration in an AI engineering team.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving skills (e.g., self-healing query pipeline, optimizing CFU detection) and an ability to work with complex systems. The experience in designing multi-tenant platforms and securing APIs suggests an understanding of operational best practices and system robustness. The mention of documentation (Swagger/OpenAPI) indicates attention to developer experience and maintainability.