AI Engineer with less than a year in NLP, Python & Data Engineering
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Fresher AI/ML engineer and Python developer (M.Sc. Data Science, CGPA 8.84) with end-to-end project experience in NLP pipelines, multi-agent LLM systems, RAG workflows, REST APIs, and ETL data pipelines using Python, FastAPI, Django REST Framework, CrewAI, LiteLLM, PostgreSQL, and Redis. Deployed an NLP embedding pipeline to AWS EC2. Writes modular, testable code (pytest). Targeting AI/ML Engineering, Data Engineering, and Junior Backend Developer roles.
Bishop Heber College
M.Sc. · Data Science
August 1, 2024 – June 30, 2026
Avvaiyar Government College for Women, Karaikal
B.Sc. · Mathematics
August 1, 2021 – June 30, 2024
IPCS Global Institute
Data Preprocessing & ML Engineering Intern
December 1, 2024 – January 1, 2025
Tirunelveli, Tamil Nadu, India
NLP Text Processing & Embedding Pipeline
June 1, 2026 – Present
Built an end-to-end NLP pipeline document ingestion, text cleaning, sentence-level chunking, and dense embedding generation using HuggingFace sentence-transformers stored in a FAISS vector index — enabling semantic similarity search over unstructured text. Exposed the pipeline as a FastAPI REST endpoint accepting text/PDF input; deployed to AWS EC2 with pytest unit tests validating chunking logic and embedding consistency, simulating a production-grade NLP microservice.
AI Multi-Agent Research & Article Generation System
June 1, 2026 – Present
Designed a CrewAI multi-agent pipeline (Researcher, Planner, Writer) with sequential task orchestration and per-agent NLP preprocessing (input parsing, chunking, structured prompt construction) - automating article generation from raw topic to publication-ready output, eliminating manual research-to-draft effort. Integrated Anthropic Claude via LiteLLM with prompt engineering and context chaining for coherent multi-agent outputs; architected a modular system with independently configurable agent roles and prompts, reducing adaptation time for new content domains.
Insurance Quote REST API
June 1, 2026 – Present
Engineered a DRF REST API for insurance premium computation; modelled relational data in PostgreSQL using ORM features (OneToOne, JSONField, ChoiceFields) and integrated Redis caching (15-min TTL) - eliminating redundant DB queries and improving repeated-request API throughput. Applied modular MVC architecture separating models, serializers, services, and views; wrote pytest unit tests across all endpoints achieving 100% pass rate — ensuring regression safety and a documented test baseline for future extensions.
View ProjectPython Development and Data Science: Variables and Data Types
Udemy
June 1, 2026 – Present
AI Fluency: Framework & Foundations
Anthropic Education
June 1, 2026 – Present
AI Fluency for Students
Anthropic Education
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in AI/ML and backend development, aligning well with an AI Engineer role. The diversity of projects (NLP pipeline, multi-agent system, REST API) shows a broad technical curiosity and ability to apply skills across different domains. The pursuit of a Master's in Data Science and relevant certifications further indicates a commitment to continuous learning and growth, which is a positive cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving and adaptability. The mention of 'modular system with independently configurable agent roles and prompts' suggests an understanding of flexible and maintainable architectures. The resume also lists communication, teamwork, and time management as soft skills, which are crucial for operational fit in a team environment.