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Python Full-Stack Engineer Intern (AI) (Remote, 6 Months)

Python Full-Stack Engineer Intern (AI) (Remote, 6 Months)

Basal AIShimoga, IN
3 days ago
Job type
  • Remote
Job description

Python Full-Stack Engineer Intern (AI)

We are looking for a passionate Python Full-Stack Engineer Interns who enjoys building modern, scalable applications and is excited to work on AI-powered software products. You will collaborate with senior engineers to develop backend services, front-end interfaces, secure APIs, and AI features leveraging LLMs, vector databases, and generative models.

Company : Basal Analytics (Basal AI)

Location : Remote (India)

Duration : 6 Months (Full-time Internship)

Compensation : Paid Internship (Monthly Stipend Provided)

Experience Required : 4-6 Months Internship

Responsibilities : You will work on :

  • Backend development using FastAPI (preferred) or Flask / Django
  • REST API design and development
  • MongoDB schema design, aggregations, indexing, and performance tuning
  • Redis for caching, rate limiting, and session management
  • Background task frameworks : Celery, RQ, APScheduler, or similar
  • Async programming and concurrency patterns
  • OAuth 2.0, JWT, or SSO authentication
  • Integrating external APIs (HTTPX / Requests, webhooks, retries, pagination)
  • Basic frontend work with React or Next.js (good to have)
  • AI integration using OpenAI, LangChain, vector databases, and embeddings

Required Skills :

  • Strong Python fundamentals
  • Experience with FastAPI or Flask / Django
  • REST API development
  • Basic knowledge of MongoDB and Redis
  • Git / GitHub experience
  • AI Integration Responsibilities

    You will work on real AI feature development, including :

  • Using OpenAI / Gemini / Anthropic APIs
  • Prompt engineering & LLM fine-tuning
  • RAG pipelines with embeddings + vector DBs (Pinecone, Qdrant, Weaviate, Chroma)
  • AI chatbots, assistants, and workflow automation
  • Text classification, summarization, entity extraction, and semantic search
  • LLM Ops : latency, cost, safety, and prompt optimization
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