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Software Engineer with 7+ years in Python, AI/ML & Cloud Ecosystem
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Assessing your cultural and operational fit
Experienced Senior Software Engineer with a proven track record of 7.9 years, specializing in Python development, AI/ML solutions, and cloud architecture, particularly on AWS. Adept at building scalable, event-driven microservices, implementing RAG systems for document classification, and optimizing application performance. Certified AWS Developer with a strong background in leading containerized microservices development and automating data pipelines for complex workflows.
St.Joseph's College Of Engineering
BE-ECE
January 1, 2014 – January 1, 2018
Thomson Reuters
Senior Software Engineer
April 1, 2023 – Present
India
Thomson Reuters
Software Engineer
July 1, 2021 – March 1, 2023
India
Jean Martin Inc.
Software Engineer
July 1, 2018 – June 1, 2021
India
The Complete Agentic AI Engineering Course
Unknown
October 1, 2025 – Present
AWS Certified Developer - Associate
Amazon Web Services
November 1, 2022 – Present
Cultural Fit Analysis
The candidate's experience across multiple roles at Thomson Reuters, coupled with their earlier role at Jean Martin Inc., shows adaptability and growth within organizations. Their involvement in developing shared infrastructure and establishing standards indicates a proactive approach to improving team efficiency and fostering a collaborative environment. The breadth of skills, from core development to AI/ML and cloud infrastructure, suggests a continuous learning mindset and a willingness to embrace new technologies, which aligns well with dynamic, innovation-driven cultures.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through performance optimization and complex system design. Their experience in leading development and establishing standards suggests good leadership potential and a collaborative mindset. The focus on security best practices and comprehensive testing indicates a detail-oriented and quality-conscious approach to software development. The candidate's work on shared infrastructure modules points to an understanding of operational efficiency and reusability.