Agentic AI & GenAI Engineer

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Skills you'll use

What you'll do

• 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:

Who can apply

• Debug, troubleshoot, and resolve performance bottlenecks in applications.
• 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.

About Sutherland

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