AI Engineer with less than a year in backend development and LLM-powered applications.
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Software Engineer building practical, production-style applications powered by LLMs – including domain-specific reasoning systems, structured output generation, and prompt engineering pipelines. Backed by hands-on backend development experience (Go, Node.js, Python/Flask), with a focus on making AI outputs reliable, structured, and safe to use in real workflows.
Cochin University of Science and Technology
Master of Science · Software Application Development
July 1, 2023 – May 1, 2025
KMEA College of Arts and Science
Bachelor of Computer Applications
June 1, 2020 – April 1, 2023
Seeroo IT Solutions
Software Engineer Intern
January 1, 2025 – May 1, 2025
Cochin, Kerala, India
Seeroo IT Solutions
Flutter Developer Intern
May 1, 2024 – July 1, 2024
Cochin, Kerala, India
Doctor BRAHMO – India-Specific Clinical AI System
June 24, 2026 – Present
Built a clinical decision-support system for diabetes and cardiovascular care for a healthcare-sector technical assessment, modeled on RSSDI/CSI treatment guidelines. Designed a drug safety engine covering eGFR/CKD-EPI renal dosing, drug-drug interaction checks, heart failure flags, CHA2DS2-VASc scoring, and allergy alerts across 30 India-specific drugs with verified pricing. Used Groq's Llama 3.3 70B to reason over structured clinical guideline and interaction data, returning safety-checked recommendations through an Express backend. Built a hospital formulary, a custom-patient workflow, and 6 working demo scenarios covering distinct clinical cases; delivered with a recorded technical walkthrough. Designed the guideline and interaction datasets myself (20 guideline nodes, 20 cross-condition drug interactions) to ground LLM responses in verified clinical logic rather than open-ended generation.
AI Resume Screening Assistant
June 24, 2026 – Present
Built a recruiter-facing tool that scores resume-to-job-description fit using prompt engineering against the Groq API (Llama 3.3 70B). Extracted resume text with pdfplumber and generated structured output - match score, strengths, missing skills, hiring recommendation – via a 4-layer Flask architecture (routes, extraction, prompt building, response parsing). Implemented defensive JSON parsing with markdown-fence stripping, regex fallback extraction, and type-safe coercion to keep LLM output reliable for downstream UI rendering. Covered the system with 35 passing tests spanning prompt construction, response parsing edge cases, Flask routes, and input validation.
Cultural Fit Analysis
The candidate's projects, particularly 'Doctor BRAHMO' and 'AI Resume Screening Assistant', demonstrate initiative and a proactive approach to learning and applying new technologies. The diversity of projects (healthcare, HR tech) and backend experience suggests a versatile individual who can adapt to different problem domains. The objective statement emphasizes building reliable and safe AI outputs, which aligns with best practices for responsible AI development.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to design comprehensive systems, manage project scope (e.g., designing datasets), and ensure output reliability, indicating strong problem-solving and attention to detail. The mention of client communication suggests good interpersonal skills. The focus on 'practical, production-style applications' aligns well with operational needs for deployable solutions.