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AI Engineer with less than a year in Python, AI/ML & Full-Stack Development
Software Engineer with 7+ months of production experience building and deploying end-to-end software systems across Python backends, computer vision pipelines, and full-stack web applications. Skilled in Python, FastAPI, Linux, REST APIs, PostgreSQL, Docker, and automated testing. Built and shipped systems that reduced manual effort by 60% and improved AI output accuracy by 40%. Experienced in the full software development lifecycle from requirements gathering and system design through coding, debugging, testing, and deployment. Adept at translating complex business problems into well-designed technical solutions, applying agile development practices, and collaborating across teams to deliver reliable, high-quality outcomes. Seeking an entry-level technology role where strong fundamentals, production experience, and a client-first problem-solving approach drive impact.
Maharaja Institute of Technology
Bachelor of Engineering · Artificial Intelligence and Data Science Engineering
August 1, 2021 – June 30, 2025
Digibull.ai
Software / ML Engineer Intern
August 1, 2025 – February 28, 2026
Mysore, Karnataka, India
Prompt Enhancement Framework
June 21, 2026 – Present
Designed an automated framework to evaluate, correct, and optimize AI prompts using rule-based and LLM-assisted refinement stages, improving response accuracy by 40%. Reduced manual prompt iteration cycles significantly; produced clear system design documentation and component interface specifications for team-wide reuse, demonstrating written communication and knowledge-sharing practices.
Automated Optical Inspection System
June 21, 2026 – Present
Built a real-time computer vision pipeline on Linux to detect cable assembly defects, reducing inspection time by 60%; designed the system architecture and led end-to-end development from concept to deployment. Designed a FastAPI backend with PostgreSQL for defect logging and automated alert notifications; containerized with Docker for reliable deployment across industrial environments. Executed test plans, logged defects, and debugged pipeline issues across the full development lifecycle. Addressed a critical business problem — costly manual inspection — by delivering a production-ready automated solution, demonstrating ability to convert operational requirements into reliable technology outcomes.
AI SQL Assistant
June 21, 2026 – Present
Built a full-stack web application (React + Vite + Tailwind frontend, FastAPI backend) that translates natural language to SQL and executes queries against PostgreSQL. Integrated REST APIs from Anthropic and OpenAI, implemented environment-based secrets management, and deployed the backend with proper configuration management and error handling. Functions as an AI-powered SQL generation productivity tool directly aligned with modern analytics workflows — enabling non-technical users to query databases through natural language.
Cultural Fit Analysis
The candidate's project diversity, including computer vision, natural language to SQL, and prompt optimization, shows a broad interest in AI applications. Their experience in an internship role at Digibull.ai, where they contributed to multiple impactful projects, suggests a proactive and results-oriented mindset. However, the limited professional experience (7+ months) and focus on a single company might indicate a need for broader exposure to different team dynamics and organizational cultures. The target role of 'AI Engineer' aligns well with their demonstrated skills and project work.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills by addressing critical business problems with automated solutions. Their experience in leading end-to-end development, collaborating with stakeholders, and producing system design documentation indicates good operational fit and communication skills within a technical team. The focus on iterative development and agile practices aligns well with modern engineering environments.