Role Descriptions:
Design| develop| and maintain Python-based GenAI systems and architecture Collaborate with the GenAI Architect and cross-functional teams to build and orchestrate intelligent agents. Implement Agent Factory logic for agent spawning| role management| and inter-agent communication. Develop modular| reusable| and scalable Python code integrated with AI pipelines. Optimize AI workflows for performance| scalability| and cost efficiency. Conduct prompt testing and refinement to enhance model output accuracy. Participate in code reviews| design discussions| and architecture validations. Work closely with the DevOps and cloud teams for containerization and deployment on Kubernetes. Document designs| reusable components| and reusable patterns within the GenAI solution.
Skills: Digital : Python~Generative AI~AI Agents
Experience Required: 6-8
Essential Skills:
Strong proficiency in Python with 7 years of hands-on experience. Deep understanding of GenAI concepts| LLMs| and Agentic AI frameworks (e.g.| Lang Chain| Lang Graph). Expertise in Prompt Engineering| Prompt Chaining| and leveraging APIs like| Azure OpenAI| OpenAI | Anthropic| or Hugging Face. Hands on experience of working on Agentic Patterns like ReAct| ReWoo| Experience building multi-agent workflows and orchestrations for reasoning| planning| and task execution. Experience integrating external tools or APIs with LLM agents (search| document retrieval| etc.). Experienced with MLOps| LLMOps| or prompt evaluation frameworks. Familiar with CICD pipelines and deployment Hands-on experience with containerization (Docker) and orchestration using Kubernetes. Familiarity with vector databases (Pinecone| FAISS| ChromaDB| etc.) and embedding generation. Strong understanding of REST APIs| microservices| and modular design for scalable AI systems. Exposure to retrieval-augmented generation (RAG) architectures. Proficient with version control (Git) and code review processes.
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