Surya Pratap Singh

Software Engineer

Howrah, West Bengal, India3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Hands-on experience in backend and data engineering.
Proficient in building microservices and data pipelines.
Explored Generative AI with practical implementations.

Stackforce AI infers this person is a Backend-focused Software Engineer with experience in Data Engineering and Generative AI.

Contact

Skills

Core Skills

Spring BootFastapiFrontend DevelopmentData EngineeringGenerative Ai

Other Skills

JavaCamundaRBACJWTPostgresMySQLAngular 20AutoGenLangChainSparkKafkaDebeziumAirflowDatabricksTypeScript

About

I’m a Software Engineer at the beginning of my professional journey, with an interest in backend development and building reliable software systems. I’ve worked with Spring Boot and REST APIs, and have been exposed to data engineering tools such as Kafka, Spark, Debezium, Airflow, and Databricks through projects and proof-of-concepts. I’ve also explored Generative AI concepts, including RAG-based systems, using tools like LangChain, LangGraph, AutoGen, and pgvector. I have a solid foundation in object-oriented programming, data structures, and problem-solving, and I’m eager to keep learning, improving, and contributing as I grow as a software engineer.

Experience

3 mos

Total Experience

3 mos

Average Tenure

3 mos

Current Experience

Intuit

Software Engineer

Feb 2026 – Present · 3 mos · Bengaluru, Karnataka, India · Hybrid

Hashedin by deloitte

2 roles

Software Engineer 1

Nov 2025 – Jan 2026 · 2 mos

Software Engineer Intern

Aug 2025 – Nov 2025 · 3 mos

During my SDE internship, I’ve been getting hands-on experience across the stack — backend, frontend, data engineering, and GenAI — and putting what I learn into real implementations.
On the backend, I’ve built microservices with Java, Spring Boot, and Camunda, set up RBAC with JWT, automated reporting, and connected services to Postgres/MySQL. On the frontend, I’ve worked with Angular 20 to create dynamic, reusable UI components using reactive forms, routing, and async communication.
In GenAI and Python, I’ve explored FastAPI, multi-agent systems with AutoGen, integrated MCP servers, and built RAG prototypes with LangChain, LangSmith, and Postgres (pgvector). On the data engineering side, I’ve designed pipelines with Spark, Kafka, Debezium, and Airflow, applied the medallion architecture, and worked with Databricks Delta Tables and Delta Live Tables.
I’ve also strengthened my DE skills in Palantir Foundry, using everything from Pipeline Builder and SQL-based Contour to ML deployment and ontology-driven data management — with a focus on lineage, scheduling, and monitoring.
Overall, this phase has been about not just learning tools and frameworks, but actually applying them to build real, end-to-end solutions and data-driven systems.

JavaSpring BootCamundaRBACJWTPostgres+10