Senior Python Developer (AI Integration)

TL;DR

Senior Python Developer (AI Integration): Architect and develop scalable production-grade Python applications including LLM-powered systems, RESTful APIs, and microservices with an accent on RAG pipelines, vector databases, and semantic search. Focus on designing end-to-end data ingestion, optimizing performance bottlenecks, and deploying containerized services on cloud platforms.

Location: Remote (work from home, beach, or office)

Company

hirify.global develops large-scale, production-grade intelligent systems.

What you will do

• Architect scalable Python applications, LLM-powered systems, RESTful APIs, and microservices using FastAPI, Flask, or Django
• Design and implement RAG pipelines, embedding workflows, and semantic search solutions
• Build and optimize data ingestion pipelines and background tasks with Celery, RabbitMQ, or Kafka
• Integrate LLM APIs (OpenAI, Anthropic, Azure OpenAI) into Python service architectures
• Design database schemas for relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
• Implement scalable vector databases (Pinecone, Weaviate) and resolve performance issues
• Containerize and orchestrate services with Docker and Kubernetes on AWS, Azure, or GCP

Requirements

• 7+ years software development, latest 1–2 years on AI/LLM solutions
• Expert-level Python (primary language)
• Hands-on with LLM apps, especially RAG systems
• Python web frameworks: Django, Flask, FastAPI
• Data libraries: Pandas, NumPy, Scikit-learn
• Vector databases (Pinecone, Weaviate), semantic search
• LLM APIs (OpenAI, Anthropic, Azure OpenAI)
• RESTful APIs, microservices, backend architecture
• Cloud: AWS, Azure, or GCP
• SQL/relational DBs (PostgreSQL, MySQL), messaging (RabbitMQ, Kafka), Docker
• Intermediate English or higher
• BSc/MSc in CS, Engineering, AI, or related

Nice to have

• Multi-agent AI systems
• FAISS, Milvus
• Hugging Face, fine-tuning models
• MLOps frameworks, model governance
• System architecture or team leadership
• PhD in relevant field

Culture & Benefits

• Work on one project at a time with long-term clients
• Flexible hours without time-tracking
• Indefinite contract (B2B option)
• Regular feedback, role switches, education support
• Monthly knowledge-sharing, weekly talks, brainstorming
• Referral fees