Shantanu Kumar

Software Engineer

Noida, Uttar Pradesh, India3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Developed scalable backend systems reducing data retrieval times by 20%
Integrated AI agents to automate workflows, decreasing task completion time by 40%
Built a customer feedback analysis platform processing 20M+ records

Stackforce AI infers this person is a Backend Engineer specializing in SaaS solutions with a strong focus on AI integration.

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Skills

Core Skills

PythonBack-end OperationsAi AgentsEngineeringData Analysis

Other Skills

FlaskFastAPIMongoDBCaching strategiesAutoGenMCPRESTful APIsPrompt orchestrationGCPBigQueryDataflowLookerCloud Pub/SubAgentic WorkflowsModel Context Protocol (MCP)

Experience

3 mos

Total Experience

3 mos

Average Tenure

3 mos

Current Experience

Samsung india

2 roles

Engineer

Feb 2026 – Present · 3 mos

Developing and maintaining a web portal in Flask and FastAPI, serving 20+ internal users, improving team task coordination by 35%.
Engineered scalable backend systems using Python, FastAPI, and MongoDB, reducing data retrieval times by 20%.
Integrated AI agents (Langchain and Autogen) that automated manual workflows, decreasing task completion time by 40%.
Implemented caching strategies, improving API response speed by 25%.
Designed backend architecture with system design best practices, supporting a scalable solution with 99.9% uptime.
Ensured backend engineering principles, optimizing API design and database queries, boosting overall system reliability.

FlaskFastAPIPythonMongoDBAI agentsCaching strategies+1

Intern

Aug 2025 – Feb 2026 · 6 mos

Designed and developed scalable backend services using FastAPI to power AI-driven automation and internal testing platforms.
Architected and deployed agentic AI systems using AutoGen and MCP (Model Context Protocol), enabling
multi-step autonomous workflows for test generation and execution.
Built RESTful APIs for test case generation, execution control, and result analysis, improving API testing throughput by 30%.
Developed structured prompt orchestration frameworks to standardize LLM interactions, improving execution
efficiency by 40%.

FastAPIAutoGenMCPRESTful APIsPrompt orchestrationEngineering+1

Cognizant

Data Analyst Intern

Feb 2025 – Jul 2025 · 5 mos

Built an end-to-end Customer Feedback Analysis Platform on GCP using BigQuery, Cloud Pub/Sub, Dataflow, and Looker to process feedback from surveys, social media, and support logs
Designed real-time data ingestion and transformation pipelines, reducing processing delays by 80% and efficiently handling 20M+ records
Developed 15+ KPIs and 4 interactive Looker dashboards, enabling cross-functional teams to access actionable customer insights
Implemented secure data workflows using Cloud KMS and IAM, automating SLA and sentiment monitoring across encrypted pipelines

GCPBigQueryDataflowLookerCloud Pub/SubData Analysis+1