Sravani Bhamidipaty
Backend Software Engineer • Chicago, IL • s******************@gmail.com • +12******905 • drivetube.ai/•••••
Professional Summary
Backend Software Engineer with 2+ years of experience building production microservices, APIs, and distributed systems using Java, Kotlin, and Python across AWS and Kubernetes. Delivered 15+ production services supporting 40+ internal teams, reduced production escalations by 70%, cut time-to-diagnosis by 40% via improved observability, and improved Whisper-based transcription accuracy from 70% to 90% to strengthen AI-enabled backend workflows.
Technical Skills
Programming Language: Python,Java,Kotlin,JavaScript,TypeScript,C++,C,SQL
Backend Technologies: FastAPI
Databases: MongoDB,PostgreSQL,Redis
Cloud Platforms: AWS
Version Control & Development Tools: Git,GitHub,Jupyter Notebook
DevOps & Infrastructure: Docker,Kubernetes,Terraform
Testing & QA: Unit Testing,Integration Testing
Messaging & Monitoring: Apache Kafka,Datadog,Prometheus
AI/ML Frameworks & Libraries: PyTorch,TensorFlow,Hugging Face
Generative AI & LLMs: Whisper,LLM
Vector Databases & RAG: RAG
Financial Planning & Analysis (FP&A): Performance Monitoring
Work Experience
W. W. Grainger
Chicago, IL
Software Engineer, Backend & AI Platforms (Java/Kotlin/Python)
Jan. 2024 – Present
Worked on backend and AI platform engineering for Grainger, a B2B industrial supply and e-commerce company; supported platform reliability, integrations, and AI-enabled workflows consumed by internal applications.
Tech Stack: Kotlin, Python, FastAPI, AWS, Kubernetes, Kafka, MongoDB, Datadog, Whisper, SQL
- Architected distributed backend orchestration on AWS and Kubernetes to standardize service workflows across engineering teams, enabling repeatable deployments and improving release efficiency for 40+ internal teams.
- Built and shipped 15+ production microservices and REST APIs using Python (FastAPI) and Kotlin to enable reliable service-to-service communication and support business-critical integrations.
- Refactored a Kotlin order-notification service to fix latency and error-handling failures, cutting production escalations by 70% and restoring SLA-compliant response times in peak traffic.
- Implemented Datadog monitoring and alerting across backend services, reducing time-to-diagnosis by 40% through focused metrics, synthetic checks, and structured runbooks for incident responders.
- Engineered event-driven data flows using Kafka and MongoDB to increase order visibility and processing reliability across operational systems, improving downstream processing consistency.
- Developed a Whisper-based transcription backend for call-bot workflows and improved speech-to-text accuracy from ~70% to 90% in production, strengthening AI-assisted automation and analytics.
Georgia Institute of Technology
Remote
Graduate Teaching Assistant (Part-time)
May. 2025 – Present
Provided instructional and automation support for graduate-level computer science coursework, improving grading efficiency and evaluation quality for course staff and students.
Tech Stack: Python, Unit testing, Jupyter Notebook, Git
- Deployed a Python-based grading automation system that reduced grading time per assignment from ~2 hours to ~10 minutes and standardized feedback delivery for students.
- Engineered object-oriented evaluation tooling and automated unit tests in Python to validate student submissions and reduce manual review effort across recurring assignments.
- Created reusable test harnesses and documentation to help graders run consistent evaluation pipelines, improving grading reliability and onboarding speed for course staff.
- Collaborated with instructors to refine assignment rubrics and automated checks, increasing consistency of grading outcomes and accelerating student turnaround.
Outlier
Chicago, IL
AI Model Trainer (Java Evaluation Tooling)
May. 2024 – Aug. 2024
Worked on evaluation tooling and quality assessment for code- and reasoning-focused AI models at an education-technology company, supporting model improvement cycles.
Tech Stack: Java, Model evaluation tooling, Test automation, Scoring taxonomies
- Developed Java-based evaluation tooling for code-generation outputs to identify recurring logical errors, contributing to a measured 18% increase in math-reasoning model precision.
- Operationalized evaluation test suites and scoring taxonomies for reasoning and code outputs to standardize model assessment and accelerate iteration feedback loops.
- Integrated automated evaluation pipelines into the model development workflow to provide faster, repeatable quality signals for model tuning and dataset curation.
- Documented evaluation criteria and produced structured error analyses to guide engineers and data scientists in targeted model improvements.
Google
Chicago, IL
Data Analyst Intern
May. 2023 – Jun. 2023
Conducted user research and usability testing to inform product decisions at Google, producing actionable insights for product and UX teams.
Tech Stack: Usability testing, User research, Data analysis
- Conducted user research with 100+ participants and executed 35+ usability tests to surface usability issues and feature improvement opportunities.
- Synthesized quantitative and qualitative test results into concise reports that informed feature prioritization and product roadmap decisions.
- Presented findings and recommended design changes to cross-functional stakeholders to accelerate UX improvements and align development priorities.
- Created structured usability test scripts and data collection templates to standardize future research efforts and enable reproducible analysis.
Projects
Mock Payment Gateway API
Tools Used: FastAPI, Kafka, Redis, PostgreSQL, Docker
- Built an event-driven payment processing platform with FastAPI, Kafka, Redis, and PostgreSQL implementing idempotent transaction handling and asynchronous workers for reliable processing.
- Designed RESTful APIs and Kafka-based messaging workflows inside a containerized microservices architecture to enable fault-tolerant communication and real-time payment tracking.
Automated Data Collection Pipeline
Tools Used: Python, Selenium
- Automated wearable data extraction with Python and Selenium, reducing retrieval time from 10 minutes to 4 minutes and improving collection efficiency by 60%.
- Processed 5,000+ data points into 20-second time-series windows to enable consistent downstream analysis.
AI-based Multi-Agent Educational Orchestrator
Tools Used: Python, LLMs
- Built a multi-agent orchestration framework using Python and LLMs to enable autonomous task planning, execution, and response generation across specialized AI agents.
- Implemented agent collaboration and workflow automation to improve task execution efficiency and support scalable AI-powered educational assistance.
Education
Georgia Institute of Technology
Master of Science, Computer Science (Artificial Intelligence Specialization) • Atlanta, GA
University of Illinois, Chicago
Bachelor of Science (Honors), Computer Science; Minor: Mathematics • Chicago, IL
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