
Creative Senior AI Engineer
1 day ago
Gen AI Architect
">Job Description:
">We are seeking a hands-on Python architect with a strong foundation in backend engineering and recent production experience in Generative AI. The ideal candidate will have 8-12 years of core Python development experience, along with 2-3 years of focused engineering work in GenAI and microservices. This role is ideal for individuals who are passionate about architecting scalable AI solutions, writing production-grade code, and enabling DevOps practices for AI-powered microservices in enterprise environments.
">Key Responsibilities:
">- Architect and implement Python-based microservices integrating GenAI 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
- Ensure system reliability, scalability, and security across GenAI-enabled services
Core Skills Required:
">- 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
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