2.5+ years at Infosys building enterprise backend systems that serve real users under real SLAs. I understand what it means to own a production service, not just ship it.

Java + Spring Boot for robust, scalable enterprise APIs. Python + FastAPI for modern async-first services. Both battle-tested across teams and deadlines.

Now, I’m deliberately moving into AI backend engineering — focusing on the infrastructure, APIs, and data pipelines that turn ML models into products that work at scale.

from dataclasses import dataclassfrom typing import List @dataclassclass RaviGupta:    # backend engineer → AI    role: str = "Backend → AI Engineer"    years_exp: float = 2.5  # years in production    stack: List[str] = ("Java", "Python", "Spring Boot", "FastAPI")    infra: List[str] = ("Docker", "CI/CD Pipelines", "PostgreSQL")    open_to: str = "AI Backend · Senior Backend"    available: bool = True     def contact(self) -> str:        return "gupta_ravi@outlook.in"