Abhay Arora

Software Engineer

Bengaluru, Karnataka, India10 yrs 8 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in full stack development with strong Java skills.
Led impactful projects at Intuit enhancing user engagement.
Passionate about driving solutions through customer empathy.

Stackforce AI infers this person is a Fintech Full Stack Engineer with expertise in impactful software solutions.

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Skills

Core Skills

Full Stack DevelopmentJava

Other Skills

system designcode reviewsSpring BootReactOracleCassandraGraphQLAWSMachine LearningSQLCPythonObject Oriented DesignData StructuresAlgorithms

About

As a passionate full stack engineer with deep customer empathy, I lead mid-sized teams and drive impactful solutions through the Learn-Teach-Learn model. At Intuit, I've been fortunate to be a part of critical projects including QuickBooks Payroll Filings, Tax Advisory services, and Cart Orchestration for professional products. Tech skills include system design, code reviews, and full stack development across Java, Spring Boot, React, (Oracle/ Cassandra), GraphQL, and AWS.

Experience

10 yrs 8 mos

Total Experience

2 yrs 7 mos

Average Tenure

2 mos

Current Experience

Agoda

Lead Engineer

Mar 2026 – Present · 2 mos

Intuit

3 roles

Staff Software Engineer

Promoted

Jan 2024 – Sep 2025 · 1 yr 8 mos

system designcode reviewsfull stack developmentJavaSpring BootReact+4

Senior Software Engineer

Promoted

Jan 2021 – Feb 2024 · 3 yrs 1 mo

Software Engineer

Nov 2018 – Jan 2021 · 2 yrs 2 mos

Paytm

Software Developer

Aug 2018 – Nov 2018 · 3 mos · Bengaluru, Karnataka, India

Finastra

Software Engineer

Jul 2015 – Jul 2018 · 3 yrs · Bengaluru Area, India

Grenoble inp - institut polytechnique de grenoble

Research Intern

Jun 2014 – Nov 2014 · 5 mos · Grenoble Area, France

Built an occupancy detection system to detect the level of occupancy in a test-bed closed office environment which also involved the collection and processing of sensor data for development of the required features. The end product was a decision tree model that could predict (with a confidence of 60-75%) the occupancy of an office space.