Jual Sunil

Backend Engineer with hands-on production experience building and deploying scalable REST APIs and modular backend systems using Python, FastAPI, and PostgreSQL. Shipped high-performance backend systems on AWS (EC2, RDS, S3) including a bulk-import pipeline processing 10,000+ records in under 60 seconds using Celery and Docker. Experienced in user-based access control (UBAC), session management, CI/CD automation, and AI/ML integrations (LangChain, Cohere).

Proven ability to own backend architecture end-to-end in a production environment.

Backend Engineer at Synexian (2025-10 – Present)

Sole backend engineer on two production applications using FastAPI, SQLAlchemy, Alembic, and Pydantic, owning end-to-end API architecture, service layer logic, schema modeling, database migrations, and deployment.

• Sole backend engineer on two production applications using FastAPI, SQLAlchemy, Alembic, and Pydantic, owning end-to-end API architecture, service layer logic, schema modeling, database migrations, and deployment.
• Architected a fine-grained User-Based Access Control (UBAC) system giving admins granular control over feature access, CRUD operation permissions, and data visibility per user.
• Produced a Markdown-compatible content management system supporting dynamic rendering and media handling.
• Assembled a bulk data ingestion pipeline processing 10,000+ records in under 60 seconds using Celery background workers, staging tables, row-level validation, partial failure handling (invalid rows rejected, valid rows committed), and duplicate control, spanning patients, treatments, invoices, dental services, and inventory.
• Formulated a modular backend architecture with clear separation of concerns to support scalability and maintainability.
• Enforced single-device login via a session control mechanism for improved account security.
• Developed backend support for analytics dashboards, including dynamic chart data and configurable visibility rules.
• Implemented a credit notes module from scratch integrated with the invoicing system to support refund workflows at a production level.
• Managed AWS infrastructure across two projects: Lightsail and EC2 (compute), RDS (database), S3 / AWS Object Storage (media and file storage), and Secrets Manager (secure configuration), with instances isolated from persistent storage.
• Containerized services using Docker and deployed a multi-service environment for shared testing and staging access.
• Personally migrated hosting from Render to AWS Lightsail, reconfiguring infrastructure, environment secrets, and deployment pipelines end-to-end.
• Wrote a shell script to fully automate deployment updates, requiring only GitHub credentials and AWS IAM details as input, eliminating manual release steps.
• Structured all backend APIs to support React frontend consumption, ensuring clean separation between frontend and backend layers.

Machine Learning Intern at Take It Smart (2023-10 – 2023-11)

Trained and deployed machine learning models using PyTorch and processed large datasets through ETL pipelines.

• Trained and deployed machine learning models using PyTorch, improving predictive accuracy on test datasets.
• Processed and validated large datasets through ETL pipelines, preparing structured inputs that improved model training efficiency.

B.E. in Artificial Intelligence & Machine Learning – AMC Engineering College, Bangalore (VTU) (2025)