Agentic AI Developer
Capgemini
Agentic AI Developer
Job Description
Agentic AI Developer
📋 Job Overview
The Agentic AI Developer role at Capgemini involves designing and developing autonomous AI architectures capable of planning, reasoning, and executing tasks using advanced LLMs and RAG pipelines. The position requires collaboration with cross-functional teams to deliver innovative AI solutions that enhance organizational capabilities. This role offers opportunities to work with cutting-edge technologies in a supportive, inclusive environment.
📍 Location: Hyderabad
💼 Experience Level: Experienced Professionals
🏢 Business Unit: I and D Global Business Line
🎯 Key Responsibilities
- Design and develop Agentic AI architectures that can autonomously plan, reason, and execute tasks
- Implement multi-agent communication protocols for agent-to-agent collaboration and coordination
- Work with Large Language Models (LLMs) such as LLaMA, GPT, etc., for language understanding, generation, and task planning
- Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance the reasoning capability of agents with external knowledge
- Perform fine-tuning of foundational models for specific domains, tasks, or use cases
- Design and experiment with lightweight models (e.g., Phi, Tiny LLMs) for efficiency in real-time or on-device scenarios
- Collaborate cross-functionally with Data Scientists, ML Engineers, and Product Teams to deliver end-to-end AI solutions
✅ Required Qualifications
- Proven experience of 6+ years in developing and deploying Agentic AI systems
- Strong experience with LLMs, particularly Meta’s LLaMA family or similar open-source models
- Hands-on experience with RAG (Retrieval-Augmented Generation) architectures and related tools like LangChain, Haystack, etc.
- Knowledge and experience with model fine-tuning using frameworks like HuggingFace Transformers, PEFT, or LoRA
- Experience in implementing agent-to-agent communication frameworks and multi-agent task handling systems
- Proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Transformers, etc.
- Familiarity with prompt engineering and chaining logic for LLMs
🛠️ Required Skills
- Agentic AI systems development and deployment
- Large Language Models (LLMs) such as LLaMA, GPT
- Retrieval-Augmented Generation (RAG) architectures
- Tools: LangChain, Haystack
- Model fine-tuning frameworks: HuggingFace Transformers, PEFT, LoRA
- Agent-to-agent communication frameworks
- Multi-agent task handling systems
- Python programming
- AI/ML libraries: PyTorch, TensorFlow, Transformers
- Prompt engineering
- Chaining logic for LLMs
- Lightweight models: Phi, Tiny LLMs
🎁 Benefits & Perks
- Range of career paths and internal opportunities within Capgemini group
- Personalized career guidance from leaders
- Comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage, and new parent support via flexible work
- Access to one of the industry's largest digital learning platforms with 250,000+ courses and numerous certifications
- Commitment to diversity, inclusion, and a sense of belonging
Locations
- Hyderabad, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Agentic AI systems development and deploymentintermediate
- Large Language Models (LLMs) such as LLaMA, GPTintermediate
- Retrieval-Augmented Generation (RAG) architecturesintermediate
- Tools: LangChain, Haystackintermediate
- Model fine-tuning frameworks: HuggingFace Transformers, PEFT, LoRAintermediate
- Agent-to-agent communication frameworksintermediate
- Multi-agent task handling systemsintermediate
- Python programmingintermediate
- AI/ML libraries: PyTorch, TensorFlow, Transformersintermediate
- Prompt engineeringintermediate
- Chaining logic for LLMsintermediate
- Lightweight models: Phi, Tiny LLMsintermediate
Required Qualifications
- Proven experience of 6+ years in developing and deploying Agentic AI systems (experience)
- Strong experience with LLMs, particularly Meta’s LLaMA family or similar open-source models (experience)
- Hands-on experience with RAG (Retrieval-Augmented Generation) architectures and related tools like LangChain, Haystack, etc. (experience)
- Knowledge and experience with model fine-tuning using frameworks like HuggingFace Transformers, PEFT, or LoRA (experience)
- Experience in implementing agent-to-agent communication frameworks and multi-agent task handling systems (experience)
- Proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Transformers, etc. (experience)
- Familiarity with prompt engineering and chaining logic for LLMs (experience)
Responsibilities
- Design and develop Agentic AI architectures that can autonomously plan, reason, and execute tasks
- Implement multi-agent communication protocols for agent-to-agent collaboration and coordination
- Work with Large Language Models (LLMs) such as LLaMA, GPT, etc., for language understanding, generation, and task planning
- Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance the reasoning capability of agents with external knowledge
- Perform fine-tuning of foundational models for specific domains, tasks, or use cases
- Design and experiment with lightweight models (e.g., Phi, Tiny LLMs) for efficiency in real-time or on-device scenarios
- Collaborate cross-functionally with Data Scientists, ML Engineers, and Product Teams to deliver end-to-end AI solutions
Benefits
- general: Range of career paths and internal opportunities within Capgemini group
- general: Personalized career guidance from leaders
- general: Comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage, and new parent support via flexible work
- general: Access to one of the industry's largest digital learning platforms with 250,000+ courses and numerous certifications
- general: Commitment to diversity, inclusion, and a sense of belonging
Tags & Categories
Agentic AI Developer
Capgemini
Agentic AI Developer
Job Description
Agentic AI Developer
📋 Job Overview
The Agentic AI Developer role at Capgemini involves designing and developing autonomous AI architectures capable of planning, reasoning, and executing tasks using advanced LLMs and RAG pipelines. The position requires collaboration with cross-functional teams to deliver innovative AI solutions that enhance organizational capabilities. This role offers opportunities to work with cutting-edge technologies in a supportive, inclusive environment.
📍 Location: Hyderabad
💼 Experience Level: Experienced Professionals
🏢 Business Unit: I and D Global Business Line
🎯 Key Responsibilities
- Design and develop Agentic AI architectures that can autonomously plan, reason, and execute tasks
- Implement multi-agent communication protocols for agent-to-agent collaboration and coordination
- Work with Large Language Models (LLMs) such as LLaMA, GPT, etc., for language understanding, generation, and task planning
- Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance the reasoning capability of agents with external knowledge
- Perform fine-tuning of foundational models for specific domains, tasks, or use cases
- Design and experiment with lightweight models (e.g., Phi, Tiny LLMs) for efficiency in real-time or on-device scenarios
- Collaborate cross-functionally with Data Scientists, ML Engineers, and Product Teams to deliver end-to-end AI solutions
✅ Required Qualifications
- Proven experience of 6+ years in developing and deploying Agentic AI systems
- Strong experience with LLMs, particularly Meta’s LLaMA family or similar open-source models
- Hands-on experience with RAG (Retrieval-Augmented Generation) architectures and related tools like LangChain, Haystack, etc.
- Knowledge and experience with model fine-tuning using frameworks like HuggingFace Transformers, PEFT, or LoRA
- Experience in implementing agent-to-agent communication frameworks and multi-agent task handling systems
- Proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Transformers, etc.
- Familiarity with prompt engineering and chaining logic for LLMs
🛠️ Required Skills
- Agentic AI systems development and deployment
- Large Language Models (LLMs) such as LLaMA, GPT
- Retrieval-Augmented Generation (RAG) architectures
- Tools: LangChain, Haystack
- Model fine-tuning frameworks: HuggingFace Transformers, PEFT, LoRA
- Agent-to-agent communication frameworks
- Multi-agent task handling systems
- Python programming
- AI/ML libraries: PyTorch, TensorFlow, Transformers
- Prompt engineering
- Chaining logic for LLMs
- Lightweight models: Phi, Tiny LLMs
🎁 Benefits & Perks
- Range of career paths and internal opportunities within Capgemini group
- Personalized career guidance from leaders
- Comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage, and new parent support via flexible work
- Access to one of the industry's largest digital learning platforms with 250,000+ courses and numerous certifications
- Commitment to diversity, inclusion, and a sense of belonging
Locations
- Hyderabad, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Agentic AI systems development and deploymentintermediate
- Large Language Models (LLMs) such as LLaMA, GPTintermediate
- Retrieval-Augmented Generation (RAG) architecturesintermediate
- Tools: LangChain, Haystackintermediate
- Model fine-tuning frameworks: HuggingFace Transformers, PEFT, LoRAintermediate
- Agent-to-agent communication frameworksintermediate
- Multi-agent task handling systemsintermediate
- Python programmingintermediate
- AI/ML libraries: PyTorch, TensorFlow, Transformersintermediate
- Prompt engineeringintermediate
- Chaining logic for LLMsintermediate
- Lightweight models: Phi, Tiny LLMsintermediate
Required Qualifications
- Proven experience of 6+ years in developing and deploying Agentic AI systems (experience)
- Strong experience with LLMs, particularly Meta’s LLaMA family or similar open-source models (experience)
- Hands-on experience with RAG (Retrieval-Augmented Generation) architectures and related tools like LangChain, Haystack, etc. (experience)
- Knowledge and experience with model fine-tuning using frameworks like HuggingFace Transformers, PEFT, or LoRA (experience)
- Experience in implementing agent-to-agent communication frameworks and multi-agent task handling systems (experience)
- Proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Transformers, etc. (experience)
- Familiarity with prompt engineering and chaining logic for LLMs (experience)
Responsibilities
- Design and develop Agentic AI architectures that can autonomously plan, reason, and execute tasks
- Implement multi-agent communication protocols for agent-to-agent collaboration and coordination
- Work with Large Language Models (LLMs) such as LLaMA, GPT, etc., for language understanding, generation, and task planning
- Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance the reasoning capability of agents with external knowledge
- Perform fine-tuning of foundational models for specific domains, tasks, or use cases
- Design and experiment with lightweight models (e.g., Phi, Tiny LLMs) for efficiency in real-time or on-device scenarios
- Collaborate cross-functionally with Data Scientists, ML Engineers, and Product Teams to deliver end-to-end AI solutions
Benefits
- general: Range of career paths and internal opportunities within Capgemini group
- general: Personalized career guidance from leaders
- general: Comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage, and new parent support via flexible work
- general: Access to one of the industry's largest digital learning platforms with 250,000+ courses and numerous certifications
- general: Commitment to diversity, inclusion, and a sense of belonging
Tags & Categories