// software engineer
Parth Shah
Building intelligent systems with Python, Django & Generative AI▊
> about
Software Engineer with 3+ years of experience in the Python/AI-ML department at Simform Solutions. I build backend systems, payment integrations, and AI-driven pipelines that ship to production.
Currently deepening my focus on Generative AI and LLM engineering — exploring retrieval-augmented generation, agentic workflows, and the tooling that makes AI systems reliable at scale.
Currently deepening my focus on Generative AI and LLM engineering.
> experience
2023.07 — present
Software Engineer
Simform Solutions LLP · Ahmedabad, GJ
- —Developed a Stripe-based subscription management service for user onboarding, billing, and automated renewals, integrating secure payment workflows and improving operational efficiency.
- —Built an AI-driven image generation pipeline with Stable Diffusion for Text-to-Image and Image-to-Image tasks, improving content workflows and scalability.
- —Implemented OAuth 2.0-based authentication supporting Sign In with Google and Sign In with Apple, enabling secure third-party login flows and reducing user onboarding friction.
2023.01 — 2023.06
IoT Engineer Intern
Simform Solutions LLP · Ahmedabad, GJ
- —Implemented an application with data storage/retrieval using SQL Server for optimized data management.
- —Gained proficiency in C, C++, and Python, and worked with IoT devices including Raspberry Pi, Arduino Uno 3, and nRF-52.
- —Implemented AWS IoT Core (Lambda functions, Greengrass framework, MQTT Protocol) for efficient, secure IoT solutions.
> skills
// languages & frameworks
PythonDjangoDRFCelery
// infrastructure & tools
DockerPostgreSQLREST APIsGit
// ai & genai
Generative AI
// ai dev tools
GitHub CopilotClaude Code
// soft skills
Client CommunicationTeam ManagementCollaborativePunctualAdaptable to New Technologies
> projects
DocuQuery
WIPA RAG-over-Stripe-docs pipeline demonstrating retrieval-augmented generation, LangChain integration, and agentic workflows.
PythonLangChainRAGStripe API