About BeGig :
BeGig is the leading tech freelancing marketplace. We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent.
By joining BeGig, youre not just taking on one roleyoure signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise.
Your Opportunity :
Join our network as an AI Backend Engineer and help power AI-driven applications from behind the scenes.
Youll be responsible for deploying and scaling language models, designing robust backend systems, and ensuring high performance, availability, and observability across environments.
Enjoy the flexibility to work remotely and choose between hourly or project-based engagements.
Role Overview :
As an AI Backend Engineer, you will :
- Serve LLM APIs : Design and deploy APIs to serve large language models efficiently and securely.
- Develop with FastAPI : Build and optimize backend endpoints using FastAPI to support real-time AI services.
- Deploy AI Models : Manage model inference endpoints, containers, and microservices for seamless integration into products.
- Cloud Infrastructure : Deploy and scale services on cloud platforms like AWS, GCP, or Azure with CI / CD automation.
- Containerization : Use Docker and Kubernetes to package, deploy, and manage scalable backend components.
- Monitor & Optimize : Set up observability tools like Prometheus and Grafana to track performance and uptime.
Technical Requirements & Skills :
Experience : Minimum 2+ years in backend engineering with exposure to AI or ML systems.API Development : Proficiency in FastAPI and Python-based API frameworks for real-time, async handling.Model Serving : Experience in LLM API deployment using tools like Hugging Face Inference Endpoints, Triton, or custom Flask / FastAPI solutions.Cloud & DevOps : Hands-on with AWS, GCP, or Azure, including CI / CD pipelines and infrastructure-as-code.Containerization : Expertise with Docker, and familiarity with Kubernetes for orchestration.Monitoring : Working knowledge of Prometheus, Grafana, or similar tools for logging and performance tracking.What Were Looking For :
A backend engineer who understands the infrastructure needs of AI-powered applications.
A freelancer comfortable with deploying large-scale systems and integrating them into live production workflows.
A performance-obsessed developer who proactively monitors and optimizes backend pipelines.
Why Join Us?
Immediate Impact : Build and manage the AI backend stack for startups pushing the boundaries of language models and automation.Remote & Flexible : Choose your working modelhourly or per projectfrom anywhere in the world.Future Opportunities : BeGig continuously matches you with AI-first product teams and backend-heavy builds.Growth & Recognition : Work in a collaborative environment that values engineering precision and infrastructure excellence.(ref : hirist.tech)