AI Engineer

𝐀𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞QAT Global is seeking for a highly skilled and passionate AI/ML professional to build a scalable AI system.You will work closely with a cross-functional team to design, deploy, and optimize an advanced AI architecture for our client, based in California.𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬• Build and optimize multi-step and multi-agent workflows for production-grade Agent and RAG frameworks for this California based client partner.• Develop scalable AI/ML solutions using Python, GCP, and LLM ecosystems.• Implement RAG pipelines and document retrieval strategies. Preprocessing, chunking, enrichment, embedding, and reranking workflows.•Design prompt templates, system instructions, and guardrails.• Integrate agents with tools, API’s, and internal services.• Optimize latency, accuracy, and token usage.• Create automated LLM evaluation and regression tests.• Deploy applications on cloud-native environments.• Work with Vector and Graph databases to enable high-performance retrieval.• Collaborate with data, cloud, and engineering teams to deliver end-to-end solutions.• Conduct performance tuning, architecture optimization, and continuous model improvements.𝐒𝐤𝐢𝐥𝐥𝐬 & 𝐐𝐮𝐚𝐥𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬• 3+ years of Python development with strong AI/ML engineering experience.• Experience monitoring, working knowledge of model versioning. Some exposure to drift detection.• Experience with one of following: LangGraph, LlamaIndex, or DSPy.• Hands-on expertise with LLM APIs. Gemini, Bedrock, Vertex AI, Claude.• Solid understanding of prompt engineering and hallucination mitigation.• Familiarity with cloud AI services.• Understanding of the fundamentals of end-to-end RAG architectures.• Understanding of Vector, Graph databases and retrieval systems such as Pinecone and Weaviate.• Exposure to LangSmith, custom evaluation pipelines.• Experience processing high-volume, multimodal documents and operationalizing data pipelines.• Strong problem-solving, architectural thinking, and production deployment experience.