Software Devleopment Engineer

Software Devleopment Engineer

Experience - 3 to 5 Years

Role - FullTime

About Venwiz

At Venwiz, we are building a next-generation enterprise B2B platform that digitizes industrial

procurement and vendor management at scale. Our platform powers complex vendor discovery, search,

procurement workflows, and AI-assisted data intelligence for large industrial enterprises.

We are looking for a highly motivated Software Development Engineer I (SDE-1) who enjoys solving

backend engineering problems, building scalable APIs, optimizing databases and search systems, and

working with modern AI infrastructure in production environments.

Technology Stack

Backend & Infrastructure: Python, TypeScript/JavaScript (Node.js), NestJS, Express.js, Flask,

FastAPI, MongoDB, Memcached (AWS ElastiCache), ElasticSearch, Vector Search Systems,

Docker, Kubernetes, Microsoft Azure, AWS, Scrapy, BeautifulSoup4, OCR Pipelines.

AI, Messaging & Distributed Systems: Azure OpenAI (GPT Models), LangGraph, Google ADK

(Agent Development Kit), Azure Service Bus, AWS SQS/SNS, KEDA, Distributed Microservices,

Event-Driven Architectures, AI Agent Workflows, Search & Retrieval Infrastructure.

Frontend: React 18 (TypeScript), Redux, Redux-Thunk, React Router v5, Sass (SCSS), Styled

Components, venwiz-ui

Responsibilities

Build, maintain, and optimize scalable backend services, APIs, distributed microservices, and

frontend applications using Python, Node.js, and React.

Develop and optimize MongoDB aggregations, ElasticSearch queries, indexing pipelines, and

large-scale retrieval workflows.

Build responsive and scalable frontend interfaces using React, Redux, and modern UI

frameworks.

Work on asynchronous event-driven architectures using Azure Service Bus, AWS SQS/SNS,

background workers, and KEDA-based scaling.

Integrate AI-powered workflows using Azure OpenAI, LangGraph, vector search, and structured

extraction pipelines.

Maintain and improve scraping, OCR, and document ingestion systems for processing structured

and unstructured enterprise data.

Write clean, production-grade code with strong focus on testing, debugging, observability,

performance, and maintainability.

What We Look For

Strong fundamentals in backend engineering, frontend development, and data structures.

Good understanding of APIs, databases, scalable system design, and modern frontend

architectures.

Ability to debug complex issues across services, frontend applications, and distributed workflows.

Curiosity to learn modern AI infrastructure, distributed systems, and scalable web architectures.

Ownership mindset with attention to code quality, maintainability, and user experience.

Ability to work in fast-moving product environments.

Bonus Experience

Experience with ElasticSearch relevance tuning, vector search, or retrieval systems.

Exposure to LLMs, AI agents, or retrieval-augmented workflows.

Familiarity with Kubernetes, Docker, or cloud-native systems.

Experience building scraping, OCR, or large-scale ingestion pipelines.

Experience with React performance optimization or large-scale frontend systems.

Contributions to side projects, open-source work, or production systems.