Job Description
Skills:
API, Full-Stack Development, Python (Programming Language), Fast api, sql, Back-End Web Development, Front-End Development,
About DataFuel
DataFuel is an eCommerce automation and analytics platform powering real businesses at scale. Our systems process large volumes of production data and drive Decision making through reliable backend infrastructure and intelligent automation.
We are a product-first engineering team focused on building scalable systems, clean abstractions, and high-performance services. We value engineers who think deeply, take ownership, and build with intent.
About The Role
We are looking for a Backend-Focused Engineering Intern with strong fundamentals and curiosity for modern AI systems (agentic workflows, LLM-based reasoning systems, etc.).
This is not a task-based internship - you will work on real production systems, contribute to core backend logic, and help build intelligent systems that interact with data, APIs, and automation pipelines.
You Should Be Someone Who
Enjoys solving complex problems independently
Can take a problem statement and drive it to execution
Is curious about how modern AI systems are architected (not just used)
What Youll Work On
Build and extend backend services using Python + FastAPI
Design and implement APIs powering production features
Work with PostgreSQL for structured data modeling and querying
Develop asynchronous workflows and background processing systems
Contribute to systems that involve LLMs, agent workflows, and reasoning pipelines
Integrate and work with AWS services (S3, EC2, RDS, etc.)
Debug production issues and optimize performance bottlenecks
Collaborate across backend + frontend (TypeScript) for feature delivery
Write clean, testable, and maintainable code
What Were Looking For
Core Requirements
Strong fundamentals in Python
Good understanding of backend development (FastAPI / Flask / Django)
Solid grasp of APIs, HTTP, and web architecture
Working knowledge of SQL and relational databases
Ability to debug, reason, and think in systems
Comfortable using Git and version control
AI / Systems Thinking (Important)
Basic understanding of LLMs and how they are used in applications
Familiarity With Concepts Like
Prompting / structured outputs
Agent workflows (planning execution iteration)
Tool usage / function calling
Interest in building AI systems, not just consuming APIs
Mindset (Very Important)
High ownership - you can take a problem and drive it end-to-end
Ability to work with minimal hand-holding
Strong problem-solving attitude
Willingness to learn fast and adapt in a production environment
Nice to Have (Bonus)
Experience with async Python / concurrency
Exposure to AWS or any cloud platform
Understanding of Docker / deployment basics
Familiarity with TypeScript or frontend basics
Interest in system design and scalability
What Youll Gain
Work on a live production SaaS produc
Hands-on experience with scalable backend systems
Exposure to real-world AI system design (agentic workflows, reasoning systems)
Mentorship from experienced engineers
Opportunity for full-time conversion based on performance
A steep learning curve - technically and professionally
Who Should Apply
This Role Is Ideal For Someone Who
Has built a few projects and wants to go deeper into real systems
Is not satisfied with tutorials and wants real engineering challenges
Wants to work at the intersection of backend systems + applied AI
