
Full Stack Engineer
1 day ago
About Us
At Devsarch, we engineer scalable digital products and enterprise solutions while pushing
boundaries with next-gen AI. We're looking for a Fullstack Engineer (React + Python) to join
our team someone who can build robust, production-grade applications end-to-end, while
also engaging with AI/LLM integrations when needed.
About the Role
This is primarily a fullstack engineering role with a strong emphasis on building scalable
applications using React (frontend) and Python/FastAPI (backend). While your main focus
will be delivering high-quality software, you will also collaborate with other engineers to integrate
AI/LLM capabilities into production systems.
Key Responsibilities
- End-to-end software delivery: Build and maintain robust, production-ready web
- applications using React (frontend) and Python (FastAPI) (backend).
- Frontend development: Create clean, efficient, and user-friendly React components,
- ensuring seamless UI/UX.
- Backend & APIs: Design and implement RESTful APIs, optimize performance, and ensure scalability.
- Data handling: Build simple pipelines to process, store, and retrieve data effectively.
- Reusable capabilities: Contribute to building shared services, libraries, and components that accelerate development across teams.
- Collaboration & mentorship: Participate in code reviews, share best practices, and mentor junior engineers to raise engineering standards.
- Quality practices: Write clean, well-tested, and well-documented code while following DevOps and CI/CD best practices.
What You Bring to the Table
- Fullstack expertise (core):
- Frontend: 2–3+ years of professional experience with (hooks, state management, component design, API integration).
- Backend: 2–3+ years of experience with Python, especially FastAPI, Django, or Flask.
- Databases: Proficiency with relational (PostgreSQL, MySQL) and NoSQL databases (MongoDB).
- Cloud & DevOps basics (Plus): Experience with Docker, CI/CD pipelines, logging, monitoring, and deployment best practices.
- AI/LLM exposure (plus): Experience integrating LLM APIs, vector databases, or frameworks like LangChain. Not required to be an AI specialist but not afraid of diving deep into these technologies.
- Collaboration: Strong communication skills, willingness to mentor, and ability to work across distributed teams.
- Problem-solving mindset: Proven track record of owning features end-to-end and iterating based on results.
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