Gowtham Mahadikar

AI Engineer with a strong interest in Generative AI, intelligent automation, and enterprise AI applications. Adept at translating complex business requirements into practical AI solutions and committed to continuous learning in the rapidly evolving AI landscape. Seeking full-time opportunities to build innovative products that create measurable business value.

AI Engineer Intern - Knowledgeflex Technologies PVT LTD - Bengaluru

(2025-12 - 2026-06)

• Architected and deployed a scalable SaaS platform for AI-driven meeting summarization, independently managing the end-to-end lifecycle from a React.js frontend to secure Node.js/Express.js backend APIs.
• Engineered AI workflows using Retrieval-Augmented Generation (RAG) pipelines and vector databases to automate meeting transcription and extract actionable decisions in real time.
• Built and optimized end-to-end meeting management system spanning scheduling, note-taking, automated summaries, and task tracking, enabling seamless real-time team collaboration.
• Designed and executed end-to-end cloud deployment strategies on Azure, leveraging Docker to containerize microservices and streamline scalable, production-ready infrastructure.

Prompt Engineer Intern - Daali Production (Film Industry) - Bengaluru

(2024-05 - 2025-03)

• Designed and fine-tuned prompts for GPT, DALL·E, MidJourney, and Stable Diffusion models to produce high-quality creative media assets.
• Conducted LoRA training to optimize AI models for specialized creative media use cases, improving output consistency and style fidelity.
• Leveraged Hugging Face tools and pipelines to accelerate AI-driven content creation workflows for film production.

Software Developer Intern - ContentEase.Ai - Bengaluru

(2023-11 - 2024-07)

• Developed end-to-end RAG pipelines using FAISS, Chroma, and Pinecone, significantly enhancing retrieval accuracy and contextual reasoning for enterprise applications.
• Engineered LLM-based function calling workflows to automate structured and reliable responses in production systems.
• Fine-tuned YOLO models for specialized computer vision use cases, boosting detection accuracy for niche business workflows.
• Implemented CI/CD pipelines to automate testing and deployment, reducing release cycles and improving delivery reliability.

Master of Computer Applications - Computer Applications - Dayananda Sagar Of Engineering (2022 - 2024)

Bachelor of Computer Applications - Computer Applications - RNS First Grade College (2019 - 2022)