

Method Hub
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1. 8 to 12 of total IT experience and has full exposure of end-to-end SDLC
2. 1 to 2 years of experience as Solution Architect
3. Should have basic understanding in Architecture methodologies like TOGAF
4. Should have working knowledge of working in Architecture tools like Visio or any other EA tool
5. Should have experience in delivering Architecture artifacts diagrams like Business Architecture, Application Architecture and Deployment Architecture
6. Experienced and implemented solutions for Architecture patterns like Microservices, Event driven, REST API’s
7. Ability to illicit both functional and Non-functional requirements for business
8. Able to provide Solutions to address all NFR requirements like Scalability, performance, Security, Availability (HA/DR and other concepts) and Resiliency (RTO/RPO and other concepts)
9. Understanding of various network protocols- HTTPS, TCP/IP etc., Authentication mechanisms like LDAP etc.

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Azure DE
Primary Responsibilities -
- Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
- Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure Create data models for analytics purposes
- Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations
- Use Azure Data Factory and Databricks to assemble large, complex data sets
- Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
- Ensure data security and compliance
- Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures
Required skills:
- Blend of technical expertise, analytical problem-solving, and collaboration with cross-functional teams
- Azure DevOps
- Apache Spark, Python
- SQL proficiency
- Azure Databricks knowledge
- Big data technologies
The DEs should be well versed in coding, spark core and data ingestion using Azure. Moreover, they need to be decent in terms of communication skills. They should also have core Azure DE skills and coding skills (pyspark, python and SQL).
Out of the 7 open demands, 5 of The Azure Data Engineers should have minimum 5 years of relevant Data Engineering experience.

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The Story
Founded in 2011, Poshmark started with a simple yet powerful idea in Manish Chandra's garage. Along with co-founders Tracy Sun, Gautam Golwala, and Chetan Pungaliya, Chandra envisioned a platform that would revolutionize how people buy and sell fashion. The inspiration came from seeing the potential of the iPhone 4 to create meaningful connections in the shopping experience.
What They Do
Poshmark is not just another e-commerce platform – it's a social marketplace that brings together shopping and community. Think of it as a place where social media meets shopping, allowing users to buy, sell, and discover fashion, home goods, and accessories. With over 80 million users , the platform has become a go-to destination for both casual sellers and entrepreneurial individuals looking to build their own digital boutiques.
Growth & Achievements
- Started as a fashion-only platform and successfully expanded into home goods and electronics
- Raised over $160 million in venture funding
- Achieved a successful IPO in January 2021
- Recently launched innovative features like AI-powered visual search and livestream shopping
- Built a vibrant community of millions of buyers and sellers across the country
Today, under CEO Manish Chandra's leadership, Poshmark continues to innovate in the social commerce space, blending technology with community to create a unique shopping experience. The platform's success story is a testament to how combining social connections with commerce can create a powerful marketplace that resonates with modern consumers.
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Robylon AI – Agentic Automation for Scalable Customer Support and Business Workflows
Robylon AI is a next-generation agentic AI platform that empowers businesses to automate over 90% of their customer queries and operational workflows across key communication channels; including chat, email, voice, and ticketing; while maintaining 99% accuracy from day one. Designed for scale, speed, and adaptability, Robylon combines the intelligence of large language models with the robustness of human-in-the-loop oversight to deliver enterprise-grade automation without requiring an in-house AI team.
Unlike traditional bots, Robylon operates as an agentic AI worker, meaning it can understand user intent, trigger actions across platforms, adapt to product updates, and continuously learn with minimal intervention. The system is plug-and-play, allowing deployment within minutes and integrations with existing tools and systems. Businesses can automate complex, multi-stage tasks and respond to customers in natural language, across multiple languages, and without scripting every possible input.
One of Robylon’s key differentiators is its transparent pay-per-resolution model. Instead of paying for seats or vague automation tiers, companies only pay for successful outcomes; making ROI instantly measurable and aligning cost with value. With this model, companies typically reduce support costs by 30% or more, while freeing up internal teams from repetitive, low-value tasks.
Key features include:
Agentic AI Workers that mirror human workflows
No-code automation builder for fast task recording and deployment
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Scheduler and bulk action tools to manage high volumes efficiently
Actionable analytics for continuous optimization
Robylon is ideal for customer support teams, product-led growth companies, operations, HR, and marketing teams looking to scale their services without scaling headcount. As AI becomes central to enterprise growth, Robylon positions itself as a mission-critical tool for forward-thinking teams that want to enhance productivity, improve customer experience, and make intelligent automation a core business advantage.
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