Agentic Ai

3 weeks ago

Noida India R Systems Full time

Job Description Your Role and Impact GenAI / Agentic AI Engineer (46 Years Experience) Key Skills & Responsibilities - Strong expertise in Prompt Engineering for LLMs and SLMs. - Hands-on experience with SLMs and CrewAI for building and orchestrating multi-agent workflows. - Proficiency with Agentic AI frameworks (LangChain, LangGraph, etc.) and Generative AI solutions. - Experience in DevOps / LLMOps / MLOps, covering deployment, monitoring, observability, and CI/CD for AI systems. - Skilled in scalability and orchestration using Docker, Kubernetes, and Cloud / On-Prem environments. - Good understanding of the Azure , AWS AI/ML stack for enterprise-grade deployments. - Strong foundation in System Design & Architecture for distributed AI solutions. - Solid programming background with conceptual programming and best engineering practices. Your Contribution Roles & Responsibilities: GenAI / Agentic AI Engineer - GenAI / Agentic AI Development - Design, develop, and deploy agentic AI workflows using frameworks like CrewAI, LangChain, LangGraph, and custom orchestration layers. - Build and fine-tune SLMs and LLMs for task-specific use cases (retrieval, summarization, reasoning, decision support). - Implement prompt engineering & prompt chaining strategies for reliability and scalability. - System Architecture & Design - Contribute to AI solution architecture ensuring modular, scalable, and cloud-native designs. - Integrate AI components with enterprise systems, APIs, and external data sources. - Develop RAG pipelines, vector database integrations (Pinecone, Weaviate, FAISS), and multi-agent systems. - MLOps / LLMOps / DevOps - Own end-to-end lifecycle management: model training, testing, deployment, monitoring, and upgrades. - Implement observability & telemetry (latency, bias, drift detection, performance monitoring). - Ensure CI/CD pipelines for AI models and services with Docker, Kubernetes, and GitOps practices. - Cloud & Infrastructure - Deploy AI workloads on Azure AI/ML stack (Azure OpenAI, Cognitive Services, Azure ML). - Optimize AI solutions across cloud and on-prem environments for cost, performance, and security. - Ensure high availability and scalability of AI services. - Governance & Risk Management - Implement guardrails, safety checks, and compliance frameworks for responsible AI. - Conduct bias testing, red-teaming, and stress testing for models and agents. - Document AI system behavior, data lineage, and model decisions for audit readiness. - Collaboration & Knowledge Sharing - Work closely with data scientists, solution architects, and business stakeholders to translate requirements into agentic AI solutions. - Provide technical mentorship on SLMs, agent orchestration, and AI system design. - Support POCs, client demos, and technical workshops showcasing AI capabilities.

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