AI Native Engineer

Location: Bengaluru

Work mode: Remote

Type: Full time

Experience: 2–3 years

Key Skills: Python, AI/LLM Agents, LangChain/LangGraph, RAG & Vector Databases, FastAPI & Async Programming, React & API Integration, Azure OpenAI, CI/CD Pipelines, Docker & Containerization, GitHub Copilot & AI-SDLC Tools.

VisioGen is building the future of AI-powered healthcare by developing human-verified clinical communication solutions for ophthalmology practices. We combine cutting-edge Generative AI with clinical expertise to build scalable, production-ready applications that enhance patient engagement and improve healthcare delivery.

We're looking for a hands-on developer to help build the AI agents and automations that make our software development lifecycle faster and more efficient. You'll work closely with the Lead Developer to turn identified friction points into working, production-grade agents, moving fast from prototype to deployment.

What you'll do

• Build agentic solutions: implement, test, and deploy AI agents and automations scoped by the Lead Developer, using skills, MCP, workflow automation, and process tooling.
• Support release gate automation: help build and maintain agents integrated into the Software Development Process (SWDP) release controls.
• Build support agents: contribute to KB-driven RAG systems and internal-team-facing agents (e.g., Product Support).
• Instrument metrics: help build and maintain product and engineering SLI/SLO instrumentation defined by the Lead Developer.
• Contribute to analytics: support conversational and forensic data analysis to surface insights and adoption friction.
• Own execution quality: write clean, tested, production-grade code and iterate quickly based on feedback.

What we're looking for

• 2-3 years of hands-on development experience, Python-first (FastAPI, async, scripting, data parsing, Pydantic).
• Working experience with AI/LLM-powered agents or tooling, production or strong project/prototype experience.
• Familiar with GitHub Copilot and other AI-in-SDLC tooling.
• Exposure to LangChain/LangGraph or similar agentic frameworks.
• Full-stack capable, comfortable in UI (React), backend services, and API integrations.
• Working knowledge of RAG pipelines and vector databases; familiarity with LLMs and the Azure AI ecosystem (Azure OpenAI, etc.).
• Familiarity with CI pipelines (Bitbucket, GitHub Actions, GitLab CI, Jenkins) and containerization (Docker).
• Self-driven with a bias to action; comfortable taking direction and running with it.
• Able to collaborate effectively with the Lead Developer and other engineering teams.