Chennai · Senior
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AI Engineer Role Overview We are seeking experienced professionals to design, develop, and deploy Agentic AI solutions integrated with Google Cloud Platform (GCP) Big Data ecosystems. The role involves building LLM-powered multi-agent systems, implementing Retrieval-Augmented Generation (RAG) pipelines, developing scalable backend services, and delivering robust enterprise-grade AI applications on Google Cloud. Key Responsibilities • Design and develop Agentic AI workflows using enterprise-grade frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar platforms. • Build and orchestrate multi-agent systems for reasoning, planning, task decomposition, and tool execution. • Develop Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search techniques. • Design, build, and optimize scalable AI applications using Python and modern LLM frameworks. • Develop RESTful APIs and microservices using FastAPI, Flask, or similar backend frameworks. • Fine-tune and customize Large Language Models using LoRA, PEFT, QLoRA, and related techniques where required. • Integrate AI solutions with GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Functions, and Vertex AI or similar cloud exposure is mandatory. • Deploy, monitor, and manage AI/ML models on Vertex AI or similar platforms. • Build data processing and feature engineering pipelines for AI applications. • Perform prompt engineering, output evaluation, guardrail implementation, and hallucination mitigation. • Implement observability, logging, monitoring, and performance optimization for AI workloads usisng tools like Dynatrace or any evaluation framework like langsmith. • Containerize applications using Docker and support deployments on Kubernetes (GKE) environments. • Collaborate closely with Data Engineers, Platform Teams, Product Owners, and Business Stakeholders. • Ensure performance, scalability, reliability, security, and maintainability of AI solutions throughout their lifecycle.
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