Data Scientist -Agentic AI, RAG Architectures (6-9 yr)

Required Travel :Minimal \n \nLocation: :[[reqLocation]] \n\n## Who are we?\n\nAmdocs helps the world\u2019s leading communications and media companies deliver exceptional customer experiences through reliable, efficient, and secure operations at scale. We provide software products and services that embed intelligence into how work runs across business, IT, and network domains \u2013delivering measurable outcomes in customer experience, network performance, cloud modernization, and revenue growth. With our talented people, and more than forty years of experience running mission-critical systems around the globe, Amdocs runs billions of transactions daily. Our technology is relied on every day, connecting people worldwide and advancing a more inclusive, connected world. Together, we help those who shape the future to make it amazing. Amdocs is listed on the NASDAQ Global Select Market (NASDAQ: DOX) and reported revenue of $4.53 billion in fiscal 2025. For more information, visit www.amdocs.com\n\nAt Amdocs, our mission is to empower our employees to \u0027Live Amazing, Do Amazing\u0027 every day. We believe in creating a workplace where you not only excel professionally but also thrive personally. Through our culture of making a real impact, fostering growth, embracing flexibility, and building connections, we enable them to live meaningful lives while making a difference in the world.\n\n## In one sentence\n\nWe are seeking a senior Data Scientist with deep expertise in Large Language Models (LLMs) and Agentic AI systems to lead the design and implementation of enterprise\u2011scale Generative AI platforms. This role focuses on advanced LLM architectures, Retrieval\u2011Augmented Generation (RAG), agent orchestration, and LLMOps, enabling secure, scalable, and production\u2011ready GenAI solutions.\n\nThe role operates at the intersection of data science, AI engineering, and enterprise architecture, with accountability for technical direction, solution robustness, and alignment with organizational GenAI strategy.\n\n## What will your job look like?\n\n * Lead the design and delivery of Agentic AI solutions using GPT\u2011, Claude\u2011, or equivalent LLM\u2011class models.\n * Architect and scale Retrieval\u2011Augmented Generation (RAG) systems for complex enterprise knowledge and workflow use cases.\n * Design and oversee multi\u2011agent systems, including orchestration, tool invocation, memory management, and context handling.\n * Build, deploy, and maintain MCP (Model Context Protocol) servers or equivalent runtime components to support agent\u2011based architectures.\n * Define and apply advanced prompt engineering strategies, including evaluation, optimization, and robustness techniques.\n * Establish and operate LLMOps frameworks, covering model lifecycle management, monitoring, observability, and performance evaluation.\n * Contribute to and influence enterprise GenAI architecture, ensuring scalability, security, governance, and compliance.\n * Act as a technical mentor and thought partner for engineers and data scientists working on GenAI initiatives.\n * Collaborate with platform, security, legal, and architecture teams to enable responsible and compliant AI adoption.\n\n\n\n## All you need is...\n\n * 6\u20139 years of professional experience in data science, applied AI, or machine learning roles.\n * Deep hands\u2011on experience with Large Language Models (e.g., GPT, Claude, or similar).\n * Proven track record of designing and delivering Agentic AI systems in production environments.\n * Strong expertise in RAG architectures, including vector databases, retrieval strategies, and hybrid search approaches.\n * Experience building or operating MCP servers or similar agent runtime and orchestration layers.\n * Advanced skills in prompt engineering, prompt evaluation, and LLM behavior tuning.\n * Practical experience with LLMOps, including deployment, monitoring, governance, and continuous improvement.\n * Strong understanding of enterprise GenAI architecture, including security, compliance, and scalability considerations.\n\n\n\n* * *\n\n## Nice to Have\n\n * Experience with cloud-based AI platforms (AWS, Azure, or GCP).\n * Exposure to knowledge graphs, semantic search, or enterprise data platforms.\n * Experience working in large-scale enterprise or telecom environments.\n * Familiarity with responsible AI, model governance, or regulatory compliance frameworks.\n\n\n\n## Why you will love this job:\n\nLead and shape next-generation Agentic AI platforms with enterprise-wide impact.Work on complex, real-world GenAI challenges at scale.Influence technical direction and AI architecture across the organization.Grow within a future-ready role architecture that values deep expertise, ownership, and innovation .\n\nAmdocs is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering a diverse and inclusive workforce\n