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Software Engineer with 4+ years in Full-Stack Development, ML, and Automation
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer skilled in full-stack development, ML, and automation, delivering high-quality solutions in fast-paced, collaborative environments. Seeking a challenging role to leverage and enhance technical skills while contributing to organizational success.
VIT University
M.Tech · Computer Science and Engineering
August 1, 2018 – June 30, 2020
Adhiyamaan College of Engineering
B.E · Computer Science and Engineering
August 1, 2014 – June 30, 2018
EagleBurgmann KE Private Limited
Software Engineer
January 1, 2023 – Present
Chennai, Tamil Nadu, India
L&T Technology Services
Engineer
January 1, 2021 – January 1, 2023
Mysore, Karnataka, India
ML-Driven Product Recommendation Engine
February 1, 2025 – May 1, 2026
Built an ML-based recommendation system using Python (Pandas, Scikit-learn), improving product suggestion accuracy by ~15% based on user interaction and purchase history. Exposed prediction services via FastAPI, supporting real-time inference for internal applications.
Agentic AI-Driven Mechanical Seal Recommendation System
February 1, 2024 – May 1, 2026
Designed an agentic AI system using Python, FastAPI, MCP, and LangGraph to analyze requirements and recommend optimal mechanical seals, improving recommendation relevance by ~20%. Built and maintained knowledge graphs (10k+ entities and relationships) using Neo4j and Ontotext GraphDB, leveraging RDF/OWL ontologies for domain modeling and semantic reasoning. Implemented Cypher and SPARQL queries to enable explainable AI (XAI), increasing transparency in decision workflows for engineering teams. Integrated with Azure OpenAI Service for LLM-powered reasoning.
CASS (Computer-Aided Seal Solution) & CASS Dashboard
May 1, 2023 – May 1, 2026
Developed a form-driven seal selection system using Angular and .NET, streamlining workflows and reducing manual configuration time by ~30%. Built interactive dashboards and integrated backend APIs to visualize data and streamline seal management workflows. Configured and maintained Azure DevOps CI/CD pipelines for automated builds, testing, and multi-environment deployments.
LangChain- Develop AI Agents with LangChain & LangGraph
Udemy
May 1, 2026 – Present
Microsoft Azure Fundamentals
Microsoft
May 1, 2026 – Present
MCP Crash Course: Complete Model Context Protocol
Udemy
May 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from traditional full-stack enterprise applications to cutting-edge agentic AI systems and ML recommendation engines, indicates a strong drive for continuous learning and embracing new technologies. Their focus on delivering solutions that "streamline workflows" and "improve recommendation relevance" suggests a product-oriented mindset. The stated career objective aligns with contributing to organizational success, making them a good cultural fit for a team seeking innovative and impactful engineers.
Soft Skills & Operational Fit
The candidate demonstrates a results-oriented approach, focusing on quantifiable improvements (e.g., "streamlining workflows," "reducing manual configuration time," "improving recommendation relevance"). Their work on "explainable AI (XAI)" suggests an understanding of transparency and user trust in complex systems. Experience in "fast-paced, collaborative environments" indicates adaptability and teamwork. The ability to integrate diverse technologies (full-stack, AI, knowledge graphs) points to strong problem-solving and architectural thinking.