Headline

Software Engineer | Distributed Systems & Microservices | AWS • Python | Data and Analytics Platforms | AI/ML Infrastructure | Ex-Carl Zeiss

About

Software Engineer | Backend & Full-Stack | AWS | AI/ML Software Engineer currently working as a contractor at ZS Associates, building scalable, HIPAA-compliant systems on AWS for the Patient Analytics Hub (PAH) and Patient Data Hub (PDH) products. I specialize in designing and delivering end-to-end features across backend, cloud infrastructure, and data systems. Over the last few years, I’ve led multiple production releases, reduced infrastructure costs by 65%, and built systems that improve reliability and self-service capabilities for clients. Key areas of work: • Event-driven architectures and centralized logging (Event Emission SDK + DQLogger) • AI-powered agents using Amazon Bedrock for log summarization and BRE explanation/creation • Anomaly Detection frameworks on Amazon SageMaker • Performance optimization of large-scale EMR Spark pipelines and PostgreSQL/Redshift tables • Cloud cost optimization, CI/CD improvements, and Angular frontend upgrades. Previously at Carl Zeiss, I worked on computer vision and full-stack applications, progressing from Intern to Senior Associate Software Engineer. I enjoy owning features from system design through deployment and monitoring, and I’m particularly interested in building reliable data platforms, AI-assisted tools, and cost-efficient cloud systems. Open to opportunities in Backend Engineering, Full-Stack Engineering and Cloud/AI roles.

Location

Pune City

AI stack

claude code

kiro

langgraph

ollama

Amazon Q Developer

Guardrails AI

Work experience

Software Engineer at RSquareSoft Technologies, Oct 2024 - Present · 2 yrs 1 mo, Pune District, Maharashtra, India, Working as a contracted Software Engineer at ZS Associates on the Patient Analytics Hub (PAH) and Patient Data Hub (PDH) products. Key Contributions: • Led releases R2–R5 of ZS’s Patient Analytics Hub (PAH). Recognized by ZS leadership for strong ownership on R4 delivery and critical security fixes in R5. • Designed and built an end-to-end Event Emission SDK with backend APIs and Angular frontend. Extended it into DQLogger, a centralized event-logging system that traces every step of an EMR pipeline run — significantly reducing root-cause investigation time. • Developed a complete Anomaly Detection framework on Amazon SageMaker with pluggable detectors (SLA-breach detection, Isolation Forest, and seasonality-aware trend analysis). • Built HIPAA-compliant AI agents on Amazon Bedrock for EMR log summarization with ChatGPT-style intent routing between “Explain BRE” and “Create BRE” agents. • Contributed to the design and partial development of Data Explorer — an interactive SQL query interface featuring Monaco Editor, Visual Query Builder, AI-assisted SQL generation running over WebSocket with Trino on EMR. • Integrated Power BI dashboards into the Patient Data Hub (PDH), enabling users to view live reports without leaving the platform. • Developed a feature for clients to retrieve Slowly Changing Dimension (SCD) tables and data for historical tracking and analysis. • Optimized AWS EMR Spark pipeline (EMR 7.8 + Graviton) processing 10 TB weekly — 30% efficiency gain and 38% lower S3 costs. Tuned a 100M+ row PostgreSQL/Redshift table, reducing query time from 27s to 6s (65% improvement). • Consolidated 7 AWS ECS instances into 1 and resolved critical IT Risk issues, achieving 65% infrastructure cost reduction. Upgraded frontend to Angular 19 and optimized CI/CD pipelines, cutting build time from 20 minutes to 5 minutes. • Optimized tag creation/build process by packaging Node modules and Python code to S3, reducing build time from 7–8 minutes to 4–5 minutes per run.

Senior Associate Software Engineer at ZEISS Group, Jul 2023 - Apr 2024 · 10 mos, Banglore, 1. Created a web app (Angular framework) with flask for capturing and extracting frame temple information from images, enabling users to snap photos with smartphones and utilize OCR for detailed temple data extraction, resulting in a 40% reduction in manual data entry time and a 25% increase in data accuracy. 2. Built a microservice using the Ollama framework that allows users to interact with Medllama (LLM specifically tailored for medical question answering (QA) and other healthcare-related tasks) for disease diagnosis by inputting their symptoms, achieving a 30% increase in diagnostic accuracy. Additionally, contributed to a Dockerized solution for the GPT builder within an Azure environment, improving deployment efficiency by 40%.

Associate Software Engineer at ZEISS Group, Jul 2022 - Jun 2023 · 1 yr, India, 1. Administered support for a hapi.js backend, integrating MongoDB aggregation pipelines for conditional frame scanning cost calculations, resulting in a 30% increase in query efficiency. 2. Successfully implemented Segment Anything Model (SAM) for accurate segmentation of glasses from users’ faces, achieving a 95% accuracy rate. Developed a robust solution that seamlessly adapts to various devices including iPhone, Android phones, and webcams, precisely isolating glasses from facial images captured on different devices.

Intern at ZEISS Group, Jan 2022 - Jun 2022 · 6 mos, Bangalore Urban, Karnataka, India, 1. Implemented headpose estimation technology in C++, ensuring precise alignment of the device with the user’s head position. 2. Played a key role in integrating the headpose estimation feature, which led to a 20% increase in user satisfaction and a 15% improvement in overall functionality. Actively participated in the coding process, successfully pushed the developed code to production, and created a monitoring dashboard to gain insights and receive alerts on critical bugs and issue.

Research Intern at NIT Warangal, May 2020 - Jul 2020 · 3 mos, India, Worked on recognition of COVID-19 patients with help of chest X-ray images using Deep learning model .

Core Team Lead at SCInTFIC - IIIT Naya Raipur, Sep 2019 - Jan 2020 · 5 mos, Greater Raipur Area, Sponsorship team leader

Education

undergradute, Computer Science, IIIT-Naya Raipur