
AI Engineer with 2+ years in Google Cloud Platform & Generative AI
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AI/ML Engineer with 2+ years of experience delivering end-to-end AI/ML solutions on Google Cloud Platform (GCP). Solely managed projects from planning to maintenance, achieving 67% faster customer response times, 40-70% faster medical record review, and 60% faster audits. Recognized as Best AI/ML Engineer. Skilled in MLOps, GPU-based ML training, and multi-agent AI systems, with dual GCP certifications.
APJ Abdul Kalam Technological University
B.Tech · Computer Science and Engineering
August 1, 2019 – June 30, 2023
Dinoct Solutions (US)
AI/ML Engineer
January 1, 2024 – Present
US
SpotSwift
June 24, 2026 – Present
Optimized ML training infrastructure by deploying GPU-based spot instances on GCP, reducing training costs by ~40% while maintaining performance SLAs.
Remote Heart Rate Estimation
June 24, 2026 – Present
Designed a spatial-temporal computer vision pipeline with PyTorch and OpenCV to contactless-ly estimate real-time heart rate (BPM) from facial near-infrared video sequences.
MediBrief AI
June 24, 2026 – Present
Built an NLP-based patient record summarization system using TensorFlow and Vertex AI, reducing doctor review time by up to 70% across structured and unstructured medical data.
CollabraGen
June 24, 2026 – Present
Developed a multi-agent generative AI system using LangChain and Vertex AI, enabling collaborative content generation with tool orchestration and contextual memory.
CyberIntercept
June 24, 2026 – Present
Cybersecurity Assistant 50% faster incident response, 50% workload reduction (Vertex AI, PyTorch, Kubernetes).
Automotive Intelligence Engine
June 24, 2026 – Present
Developed a multi-agent RAG system using LangChain and LangGraph to ingest, parse, and query dense, unstructured automotive engineering standards with cited references.
VigilantAudit
June 24, 2026 – Present
Audit Automation 60% faster audits, 75% fewer false positives, saved ~$30K/year.
Conversational AI
June 24, 2026 – Present
Developed a production-grade multi-turn conversational AI system with real-time contextual memory and tool orchestration (LangChain, LangGraph, GCP), supporting concurrent sessions with sub-2s response latency - designed as an enterprise Gemini-like live chat interface.
EchoStream
June 24, 2026 – Present
Designed and deployed a CRM chatbot using Vertex AI and Cloud Run, handling 1K+ queries/day, reducing customer response time by 67% through intent classification and retrieval-based response generation.
GCP Associate Cloud Engineer
Google Cloud Platform (GCP)
June 1, 2026 – Present
GCP Professional Machine Learning Engineer
Google Cloud Platform (GCP)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an AI Engineer role, particularly in an environment focused on innovation and practical application. Their diverse project portfolio, ranging from healthcare NLP to cybersecurity and automotive intelligence, showcases adaptability and a broad interest in applying AI across various domains. The leadership and mentorship experiences indicate a proactive and collaborative mindset. The focus on delivering quantifiable business value in projects aligns with a results-oriented culture.
Soft Skills & Operational Fit
The candidate's resume highlights strong problem-solving, decision-making, critical thinking, and team management skills. Their experience leading end-to-end project delivery and coordinating with cross-functional stakeholders suggests good operational fit and ability to manage project timelines and requirements. The leadership roles mentioned (TinkerHub Tech Lead, IEEE Xtreme Mentor, IoT Mentor/Coordinator) further support their capacity for collaboration and mentorship.