Sakshi Parikh

Software Engineer

Bengaluru, Karnataka, India4 yrs 10 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in building AI-driven solutions.
Proficient in real-time data processing with Flink.
Strong mentoring experience in software development.

Stackforce AI infers this person is a Full-Stack Developer with expertise in SaaS and real-time data processing.

Contact

Skills

Core Skills

Full-stack DevelopmentBack-end Web DevelopmentCoaching & MentoringJavaSpring BootAiApache FlinkInfluxdbApache Kafka

Other Skills

Go (Programming Language)Interview PreparationUpskillingAmazon SQSFastAPIPydantic AIGrafanaPySparkPostgreSQLAmazon Simple Notification Service (SNS)Amazon Web Services (AWS)Python (Programming Language)GitAWSPython

About

Hi, I am Sakshi Parikh, Software Engineer 2 [fullstack] at Intuit. I have 3 years of comprehensive experience in the software development industry and AI Agents, combined with a year-long internship stint that has helped me refine my software engineering skills. I have experience in Java, Python, AWS, Springboot, FastAPI, Flink, Spark, PostgreSQL, InfluxDB (NoSQL), Go, Flutter, Android, Splunk, flutter I am passionate about building real world problems with latest technologies

Experience

4 yrs 10 mos

Total Experience

2 yrs

Average Tenure

8 mos

Current Experience

Uber

Software Engineer II

Sep 2025 – Present · 8 mos

Back-End Web DevelopmentFull-Stack DevelopmentGo (Programming Language)

Preplaced

Long-Term Mentor

Apr 2024 – Present · 2 yrs 1 mo · India · Remote

Interview PreparationUpskillingCoaching & Mentoring

Intuit

2 roles

Software Engineer 2

Promoted

Feb 2024 – Sep 2025 · 1 yr 7 mos

Working towards building an AI agent to identify potential issue and recommend steps to rectify operational issues using various tools
Developed and Designed architectures around automating demand and supply for Intuit expert operations
Developed issue management service (Java, Springboot) to handle breaching realtime metrics and managing lifecycle of triggered issues using Grafana & AWS.
Developed Flink pipeline to handle real time events from multiple sources in config driven format and ingest into Influx timeseries db. It currently handles ~ 3.5M records per day
Performed benchmarking to identify best time-series db
Ensured operational excellence and resiliency by building backfill mechanism and manage redundancy in realtime for profitable peak metrics.
Designed and contributed towards building generic Anomaly Detection Module for Planning

Amazon SQSInfluxDBFastAPIPydantic AIGrafanaJava+11