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Data Scientist -Agentic AI, RAG Architectures (6-9 yr) (210899)

Min Experience

6 years

Location

Pune, Maharashtra, India

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

Career Opportunities: Data Scientist -Agentic AI, RAG Architectures (6-9 yr) (210899)

Requisition ID 210899 - Posted  - India - Pune

Required Travel :Minimal 
 
Location: :[[reqLocation]] 

Who are we?

Amdocs helps the world’s 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 –delivering 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 

At Amdocs, our mission is to empower our employees to 'Live Amazing, Do Amazing' 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.

In one sentence

We 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‑scale Generative AI platforms. This role focuses on advanced LLM architectures, Retrieval‑Augmented Generation (RAG), agent orchestration, and LLMOps, enabling secure, scalable, and production‑ready GenAI solutions.
The 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.

What will your job look like?

  • Lead the design and delivery of Agentic AI solutions using GPT‑, Claude‑, or equivalent LLM‑class models.
  • Architect and scale Retrieval‑Augmented Generation (RAG) systems for complex enterprise knowledge and workflow use cases.
  • Design and oversee multi‑agent systems, including orchestration, tool invocation, memory management, and context handling.
  • Build, deploy, and maintain MCP (Model Context Protocol) servers or equivalent runtime components to support agent‑based architectures.
  • Define and apply advanced prompt engineering strategies, including evaluation, optimization, and robustness techniques.
  • Establish and operate LLMOps frameworks, covering model lifecycle management, monitoring, observability, and performance evaluation.
  • Contribute to and influence enterprise GenAI architecture, ensuring scalability, security, governance, and compliance.
  • Act as a technical mentor and thought partner for engineers and data scientists working on GenAI initiatives.
  • Collaborate with platform, security, legal, and architecture teams to enable responsible and compliant AI adoption.

All you need is...

  • 6–9 years of professional experience in data science, applied AI, or machine learning roles.
  • Deep hands‑on experience with Large Language Models (e.g., GPT, Claude, or similar).
  • Proven track record of designing and delivering Agentic AI systems in production environments.
  • Strong expertise in RAG architectures, including vector databases, retrieval strategies, and hybrid search approaches.
  • Experience building or operating MCP servers or similar agent runtime and orchestration layers.
  • Advanced skills in prompt engineering, prompt evaluation, and LLM behavior tuning.
  • Practical experience with LLMOps, including deployment, monitoring, governance, and continuous improvement.
  • Strong understanding of enterprise GenAI architecture, including security, compliance, and scalability considerations.

Nice to Have

  • Experience with cloud-based AI platforms (AWS, Azure, or GCP).
  • Exposure to knowledge graphs, semantic search, or enterprise data platforms.
  • Experience working in large-scale enterprise or telecom environments.
  • Familiarity with responsible AI, model governance, or regulatory compliance frameworks.

Why you will love this job:

Lead 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 .

Amdocs is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering a diverse and inclusive workforce                      

The job has been sent to

Required Travel :Minimal 
 
Location: :[[reqLocation]] 

Who are we?

Amdocs helps the world’s 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 –delivering 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 

At Amdocs, our mission is to empower our employees to 'Live Amazing, Do Amazing' 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.

In one sentence

We 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‑scale Generative AI platforms. This role focuses on advanced LLM architectures, Retrieval‑Augmented Generation (RAG), agent orchestration, and LLMOps, enabling secure, scalable, and production‑ready GenAI solutions.
The 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.

What will your job look like?

  • Lead the design and delivery of Agentic AI solutions using GPT‑, Claude‑, or equivalent LLM‑class models.
  • Architect and scale Retrieval‑Augmented Generation (RAG) systems for complex enterprise knowledge and workflow use cases.
  • Design and oversee multi‑agent systems, including orchestration, tool invocation, memory management, and context handling.
  • Build, deploy, and maintain MCP (Model Context Protocol) servers or equivalent runtime components to support agent‑based architectures.
  • Define and apply advanced prompt engineering strategies, including evaluation, optimization, and robustness techniques.
  • Establish and operate LLMOps frameworks, covering model lifecycle management, monitoring, observability, and performance evaluation.
  • Contribute to and influence enterprise GenAI architecture, ensuring scalability, security, governance, and compliance.
  • Act as a technical mentor and thought partner for engineers and data scientists working on GenAI initiatives.
  • Collaborate with platform, security, legal, and architecture teams to enable responsible and compliant AI adoption.

All you need is...

  • 6–9 years of professional experience in data science, applied AI, or machine learning roles.
  • Deep hands‑on experience with Large Language Models (e.g., GPT, Claude, or similar).
  • Proven track record of designing and delivering Agentic AI systems in production environments.
  • Strong expertise in RAG architectures, including vector databases, retrieval strategies, and hybrid search approaches.
  • Experience building or operating MCP servers or similar agent runtime and orchestration layers.
  • Advanced skills in prompt engineering, prompt evaluation, and LLM behavior tuning.
  • Practical experience with LLMOps, including deployment, monitoring, governance, and continuous improvement.
  • Strong understanding of enterprise GenAI architecture, including security, compliance, and scalability considerations.

Nice to Have

  • Experience with cloud-based AI platforms (AWS, Azure, or GCP).
  • Exposure to knowledge graphs, semantic search, or enterprise data platforms.
  • Experience working in large-scale enterprise or telecom environments.
  • Familiarity with responsible AI, model governance, or regulatory compliance frameworks.

Why you will love this job:

Lead 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 .

Amdocs is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering a diverse and inclusive workforce                      

About the company

Software and IT services for telecommunications and media providers.

Skills

Large Language Models
RAG
MCP servers
LLMOps
Prompt engineering
Knowledge graphs
Cloud platforms (AWS/Azure/GCP)