Job Type : Full-Time / 1-Year Contract
Work Mode : Remote (Work From Home)
Experience Required : Minimum 3 years
About the Role
We are looking for a skilled Python AI Developer with solid experience in building, deploying, and maintaining AI-driven applications. You will work from prototyping to production deployment using modern AI tools and Python-based frameworks.
The ideal candidate is strong in Python, familiar with AI coding tools, and has experience developing and deploying functional application software.
Key Responsibilities
- Develop, test, and deploy AI-driven applications using Python
- Build end-to-end features from backend logic to production deployment
- Integrate third-party APIs, AI models, and automation workflows
- Use productivity tools like Replit, Cursor, and AI coding assistants to speed up development
- Work with vector stores, embeddings, LLM APIs, and Python libraries
- Optimize and maintain existing codebases and pipelines
- Collaborate with product and PM teams to convert requirements into deliverables
- Implement basic DevOps tasks related to deployment, version control, and CI / CD
- Maintain high code quality, documentation, and testing coverage
Required Skills Technical
Strong proficiency in Python (3+ years)Experience with AI tools such as Replit, Cursor, ChatGPT-based workflowsExperience building and deploying applications (web apps, APIs, bots, automation tools)Familiarity with :FastAPI / Flask / DjangoLangChain / LlamaIndex / n8n (optional but preferred)Vector DBs (Pinecone, FAISS, Chroma)REST APIs / WebhooksGit & basic DevOpsExperience with hosting / deployment platforms (AWS, Azure, GCP, Railway, Render, Vercel)Ability to build complete features independentlyUnderstands lifecycle : requirements → development → testing → deployment → maintenanceStrong problem-solving and debugging skillsAbility to work remotely with discipline and accountabilityPreferred
Experience with automation bots (Telegram, WhatsApp, Slack)Experience with Replit Deployments or serverless systemsExperience in integrating LLMs into production apps