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Agentic AI & GenAI Engineer at Sutherland – Chennai | Jobyssey

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Agentic AI & GenAI Engineer

Agentic AI & GenAI Engineer

Sutherland · Chennai, TN, in · 3 weeks ago

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Category: AI engineering

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We are looking for a skilled and delivery-focused Agentic AI & GenAI Engineer, who is passionate about developing innovative solutions using Agentic AI frameworks. The ideal candidate should have experience in designing, implementing, and optimizing Agentic workflow and building scalable, production-grade Agentic AI models.

Key Responsibilities:

Develop, test, and manage day-to-day execution of AI projects, ensuring timely delivery, quality, and alignment to architectural design.
Translate architectural blueprints into executable components, prototypes, and production-ready services.
Oversee the development of GenAI applications, RAG pipelines, and agent-based solutions using frameworks like Langchain, LangGraph and Google ADK.
Work on data preprocessing, feature engineering, and model optimization.
Optimize performance of existing Agentic AI models and pipelines.
Review code, support reusable component development, and enforce engineering best practices.
Utilize cloud-based services (AWS, Azure, or GCP) for model deployment and scaling.
Stay updated with the latest advancements in AI, ML, and data science.
Debug, troubleshoot, and resolve performance bottlenecks in applications.

Required Skills & Qualifications:

Strong proficiency in AI/ML engineering or software development using Python and its frameworks.
Experience delivering projects using GenAI, LLMs, or Transformer models and Agentic AI based solutions.
Solid understanding of prompt engineering, APIs, data preprocessing, and model integration.
Exposure to vector databases and RAG architectures for enterprise knowledge retrieval. Exposure to MCP and Agent to Agent Communication
Familiarity with SQL, NoSQL, and data warehousing solutions and ability to analyze complex datasets and derive meaningful conclusions.
Understanding of CI/CD pipelines, Docker, and Kubernetes for AI model deployment.