Engineering

• Hands-on experience in designing and building cloud-native data platforms, backend systems, and SaaS architectures on AWS.
• Expertise in high-volume event ingestion, batch and streaming data pipelines, and analytics platforms using modern lakehouse architectures such as Apache Iceberg.
• Strong background in building secure, scalable APIs and microservices, supporting multi-tenant and enterprise-grade use cases.
• Active development of internal reference platforms and demo systems that reflect real-world production challenges, including scalability, data isolation, performance tuning, and cost optimization.
• Practical implementation of Agentic AI architectures, including LLM-powered services, retrieval-augmented generation (RAG), and intelligent copilots integrated with data platforms and backend systems to automate workflows and provide actionable insights.

• SaaS companies building or scaling multi-tenant cloud platforms.
• Startups and product teams modernizing legacy data and backend architectures.
• Engineering teams handling large-scale data ingestion, analytics, and reporting.
• Organizations working with security, observability, or operational data.
• Teams looking to introduce AI-driven automation and intelligent assistants into their cloud and data workflows.

• Engineering-first approach focused on simple, maintainable, and scalable system design.
• Deep understanding of AWS services and cloud-native architectures, with practical, hands-on delivery.
• Ability to bridge data engineering, backend development, and AI-driven automation in a single cohesive solution.
• Experience with Agentic AI patterns, including event-driven agents, LLM-based copilots, and RAG-powered knowledge access.
• Transparent, pragmatic engagement style focused on long-term value, performance, and cost efficiency.

• Building internal platform foundations and reusable components for SaaS and data-driven systems.
• Developing reference architectures and demo products that mirror enterprise-scale requirements.
• Using internal platforms to strengthen delivery, support learning programs, and accelerate future Claigen products.
• Continuous focus on modern cloud, data, and AI-native system design.

Looking to design, modernize, or scale your cloud and data platform?
📧 Contact us at swayam@claigen.in