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AI Engineer with less than a year in Generative AI & LLM Platforms
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Assessing your cultural and operational fit
AI Engineer with experience building production-grade Generative AI systems, self-hosted LLM platforms, multimodal retrieval architectures, and AI-powered SaaS products. Experienced in deploying open-source LLMs using vLLM and TGI, designing OpenAI-compatible APIs and SDKs, developing scalable RAG pipelines, and integrating AI solutions into healthcare, education, and enterprise applications. Strong foundation in backend engineering, model serving, and AI infrastructure.
Marri Laxman Reddy Institute of Technology and Management
B.Tech · Computer Science (Artificial Intelligence Machine Learning)
N/A – June 30, 2026
VitaInspire Private Limited
Junior AI Engineer
January 1, 2026 – July 1, 2026
India
Self-Hosted Multimodal LLM Platform
January 1, 2026 – June 1, 2026
Built and deployed a self-hosted multimodal LLM platform using vLLM and Hugging Face TGI. Implemented advanced inference optimization techniques including Paged Attention, KV Cache management, continuous batching, and efficient GPU utilization. Designed OpenAI-compatible and Gemini-compatible API endpoints enabling seamless migration from external AI providers. Developed an internal SDK with API-key-based authentication allowing teams to consume self-hosted LLM services through a unified interface.
View ProjectLive Sync RAG Platform
January 1, 2026 – June 1, 2026
Built a production-grade Retrieval-Augmented Generation platform capable of automatically synchronizing enterprise knowledge sources in real time. Designed scalable ingestion, chunking, embedding, indexing, and retrieval pipelines supporting continuously updated knowledge bases. Implemented asynchronous document processing and semantic retrieval architecture for low-latency knowledge access.
Multimodal Video-to-Video RAG System
January 1, 2026 – June 1, 2026
Developed a multimodal AI system capable of processing training videos with or without audio and generating contextual video responses. Integrated speech extraction, semantic retrieval, embedding pipelines, LLM reasoning, and video generation workflows. Enabled interactive knowledge retrieval from large educational and training-content repositories.
AI-Powered Telehealth Platform
January 1, 2026 – June 1, 2026
Contributed to the development of an end-to-end telehealth ecosystem supporting doctors, patients, and healthcare administrators. Integrated AI-powered conversational systems, workflow automation features, and intelligent assistance capabilities. Enhanced healthcare accessibility through scalable backend services and AI-assisted interactions.
Professional Cybersecurity Certificate
June 1, 2026 – Present
Machine Learning Certification
Great Learning
June 1, 2026 – Present
Artificial Intelligence Certification
Metvy Learning
June 1, 2026 – Present
Data Science and Analytics
Simplilearn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the target role of an AI Engineer, focusing on practical applications of Generative AI, LLMs, and RAG. The diversity of projects (healthcare, education, enterprise) shows adaptability and a broad interest in applying AI solutions across different domains. However, the limited professional experience (6 months) and the fact that the candidate is still pursuing a bachelor's degree (graduating 2026) suggest a junior profile, which might not fully align with a senior-level cultural fit expectation without further validation of their depth and autonomy.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with product, engineering, and AI teams, suggesting an ability to work in cross-functional environments. Their involvement in workshops and mentoring indicates leadership potential and a willingness to share knowledge. However, without specific psychometric or English test scores, a deeper assessment of communication clarity, work attitude, stress handling, and team collaboration is not possible.