
LLM Agentic AI Developer
17 hours ago
Key Responsibilities:
- Design, implement, and optimize multi-agent RAG systems using LangGraph, LangChain, and similar agentic frameworks.
- Orchestrate and coordinate agent-based workflows, managing state and memory across agents for robust, scalable AI features.
- Integrate, tune, and maintain vector databases such as Pinecone and Weaviate for efficient semantic search and retrieval.
- Develop backend APIs and microservices in Python or , with seamless interactions with agentic pipelines and vector databases.
- Deploy solutions on AWS, leveraging services like Amazon S3, Lambda, EC2, and container orchestration tools.
- Collaborate with frontend and cross-functional product teams to deliver high-quality, reliable user experiences.
- Oversee software lifecycle, maintaining documentation, automated testing, CI/CD pipelines, and performance monitoring.
Qualifications:
- Hands-on experience designing and deploying AI/ML and RAG applications with advanced agentic frameworks (LangGraph, LangChain, CrewAI or AutoGen).
- Strong software engineering background in Python or ; familiarity with FastAPI a plus.
- Significant expertise working with vector databases, including Pinecone and Weaviate, for RAG architectures.
- Proven track record of deploying, operating, and optimizing applications on AWS (S3, Lambda, API Gateway, etc.).
- Familiar with DevOps and MLOps practices; skilled in working with cloud-native tools and services.
- Exposure to advanced agentic concepts and frameworks; familiarity with Google agentic tools is an advantage.
- Excellent communication and the ability to thrive within cross-functional teams
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