Shivam Behl

Software Engineer

India4 yrs 9 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in building distributed systems and cloud infrastructure.
Proven track record in automating cloud operations.
Strong background in machine learning and AI applications.

Stackforce AI infers this person is a Cloud Computing and E-commerce specialist with strong expertise in AI and distributed systems.

Contact

Skills

Core Skills

Cloud AutomationDistributed SystemsMicroservicesData EngineeringMachine Learning

Other Skills

Configuration ManagementAI SystemsLogging ArchitectureObservabilityAnalyticsAutomationGolanggRPCKubernetesMongoDBData IngestionSparkFlinkSQLPython

About

🎓 Thapar Alum | B.E. in Computer Engineering 💼 Where I’ve Been: - Microsoft (Sovereign Cloud) — Automating secure cloud build-up, configuration management, logging, and observability. - Zepto — Designed smooth and efficient checkout experiences for India’s fastest grocery delivery platform. - Flipkart — contributed in launch of Flipkart Home Services- built cart, invoice microservices; streamlined data pipelines; revamped a reliable task execution platform with ordered task support. 💡 What I Love: - Building distributed systems, cloud infrastructure, and high-performance platforms. - Exploring Machine Learning & Artificial Intelligence — always up for meaningful discussions and innovative applications. - Teaching & sharing knowledge: Delivered guest lectures on ML, created content for bootcamps, and love volunteering for tech education initiatives for students. ⚙️ Tech Skills & Tools: Languages: Golang, Java, Python Frameworks & Tools: Kubernetes, Spark, Flink, Distributed Systems, Cloud Automation 🤝 Let’s Connect: Always open to collaborating on challenging projects, mentoring, or exchanging ideas on AI, cloud, and system design.

Experience

4 yrs 9 mos

Total Experience

1 yr 7 mos

Average Tenure

1 yr 10 mos

Current Experience

Microsoft

Software Engineer 2

Jul 2024 – Present · 1 yr 10 mos · Remote

Core contributor to a unified configuration management platform for Microsoft Azure, reducing Sovereign Cloud build-out time and improving deployment consistency.
Designed and developed a multi-agent AI system using AutoGen to enable proactive incident detection, intelligent automation, and semi-automated onboarding workflows via pull request generation.
Led a logging architecture redesign, transitioning from runtime to compile-time logging, achieving a 30× improvement in efficiency, reducing system overhead, and enhancing scalability.
Built an end-to-end observability and analytics platform using OpenTelemetry, Azure Data Explorer, Prometheus, Grafana, and Power BI, enabling real-time monitoring, performance optimization, and data-driven operational insights.
Built an end-to-end observability and analytics stack using OpenTelemetry, Azure Data Explorer, Prometheus, Grafana, and Power BI to provide unified monitoring, performance analysis, and operational insights.

Configuration ManagementAI SystemsLogging ArchitectureObservabilityAnalyticsCloud Automation+1

Zepto

Software Engineer 2

Feb 2024 – Jul 2024 · 5 mos · Hybrid

✅ Responsible for the Cart Microservice.
⚙️ Revamped product details enrichment in Cart and brought down cart page latencies by 53%
📚 Golang, gRPC, Kubernetes, MongoDB

GolanggRPCKubernetesMongoDBMicroservicesDistributed Systems

Flipkart

2 roles

Software Engineer

Jul 2021 – Jan 2024 · 2 yrs 6 mos

🛒 Designed/Developed Cart, Checkout, & Invoicing microservices for Flipkart Home Services
🔄 Revamped Data Ingestion Pipelines using Spark & Flink CDC
⚙️ Upgraded Async Task Management for ordered task execution
Other than this have worked on optimisation engine, KEDA, externalisation initiatives etc.
📈 Results:
Helped Launch Home Services, taking Jeeves to B2C
Optimized data processing for Analytics and Reporting
Streamlined async-task execution management.

MicroservicesData IngestionSparkFlinkData Engineering

SDE Intern

Jan 2021 – Jun 2021 · 5 mos

⚙️ Improved System Reliability:
Achieved < 0.01% average error rate across 10+ micro-services.
🚀 Migration to Kubernetes:
Successfully migrated micro-services from VMs to Kubernetes.
Streamlined deployment processes, optimizing resource utilization
📈 Impact:
Enhanced on-call experience
Significantly reduced false error rates
Modernized infrastructure for scalability

Kubernetes

Infovio

Machine Learning Engineer

May 2020 – Jun 2020 · 1 mo

🤖 Designed and Implemented AutoML Library:
Led the design and implementation of an AutoML library, contributing to automated machine learning workflows.
🐍 Implemented ML and Optimization Algorithms:
Implemented machine learning and optimization algorithms from scratch in Python, showcasing strong programming and algorithmic skills.
🚀 Achievements:
Helped the creation of a robust AutoML solution.
Implemented core algorithms for enhanced functionality.
📊 Results:
Helped empower the startup's data science capabilities.
Strengthened proficiency in ML and optimization.

Machine LearningSQL