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Artificial Intelligence Lead Developer
3 weeks ago
Develop highly scalable, maintainable, and testable artificial intelligence-driven applications.
- Architect and implement microservices integrating Generative AI capabilities
- Design GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration engines
- Develop RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI/Azure OpenAI or open-source models
- Work with DevOps engineers to enable CI/CD, monitoring, and observability for GenAI pipelines
- Collaborate with ML engineers and data scientists to optimize GenAI system performance and scalability
- Lead design sessions, code reviews, and mentor junior engineers on architectural best practices
- Implement agentic workflows using Semantic Kernel, LangGraph, or similar orchestration tools
Core Skills:
- Expert-level Python development skills including experience with FastAPI, Flask, asyncio
- Strong understanding of microservices architecture and distributed systems
- Hands-on experience with GenAI tools: LangChain, LlamaIndex, Hugging Face Transformers
- Practical knowledge of deploying LLMs on cloud platforms (Azure OpenAI preferred)
- Experience with REST API design and integration with external AI services
- Familiarity with vector databases like FAISS, Pinecone, or Weaviate
- DevOps practices: CI/CD with GitHub Actions, Docker, Kubernetes, Terraform
- Proven ability to design scalable, maintainable, and testable AI-driven applications
Secondary / Nice-to-Have Skills:
- Experience with agentic orchestration systems such as Autogen, Semantic Kernel, LangGraph
- Exposure to fine-tuning open-source LLMs and deployment in containerized environments
- Understanding of AI observability, performance tuning, and system logging
- Background in MLOps and collaboration with Data Science/ML teams
- Familiarity with agile development and cross-functional engineering collaboration
