Gen AI Engineer - AD
KPMG Global Services (KGS) · Consulting & Professional Services
- Pune, Maharashtra, India
- On-site
- Posted today
- Closes today
- Data & AI
About the job
Job Title: Associate Director
Role: AI Architect
Experience: 12+ Years
About the Role:
We are seeking a Principal AI Engineer / AI Architect with extensive experience in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , and Agentic AI systems . This role requires strategic leadership , architectural design , and delivery of large-scale AI projects . You will define technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives.
Key Responsibilities:
Lead and architect enterprise-scale AI solutions leveraging LLMs, multimodal models, and advanced GenAI techniques.
Design and oversee RAG pipelines and Agentic AI frameworks for complex workflows.
Define AI architecture standards , scalability strategies, and integration patterns with cloud services.
Drive effort estimation , resource planning, and delivery timelines for large-scale AI projects.
Collaborate with senior stakeholders to propose AI-driven solutions and influence technology strategy.
Ensure compliance with security, governance, and ethical AI principles .
Oversee model deployment, model cost estimation in production environments and ensure robust monitoring.
Lead MVP development for rapid prototyping and proof-of-concept initiatives.
Mentor and guide engineering teams, fostering innovation and best practices.
Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
Generative AI: Proven experience in LLM fine-tuning, prompt engineering, and production deployment.
RAG & Agentic AI: Advanced knowledge of embeddings, vector databases (FAISS, Pinecone), and agent orchestration frameworks (LangChain, AutoGen).
Traditional ML & Deep Learning: Strong foundation in ML algorithms and deep learning architectures (CNNs, RNNs, Transformers).
Architecture & Leadership: Ability to design scalable AI architectures , manage large teams, and deliver enterprise projects.
Cloud Expertise: Strong understanding of cloud services (AWS, Azure, GCP), including compute, storage, networking, and AI-specific offerings.
MVP Development: Experience creating proof-of-concepts and MVPs for rapid prototyping and stakeholder validation.
Production Deployment: Should have proven capability to production
Excellent communication and stakeholder management skills.
Preferred Skills:
Experience with MLOps , CI/CD for AI, and multi-cloud deployments .
Familiarity with cost optimization , security best practices , and disaster recovery strategies .
Exposure to multi-modal AI , agent orchestration , and AI governance frameworks
Hands-on experience deploying AI models in production environments with monitoring and scaling strategies.
Cost Estimation: Exposure to estimating LLM model costs prior to deployment , including compute, storage, and inference optimization.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
12+ years of experience in AI/ML development, with at least 5+ years in Generative AI and advanced AI systems .
Proven track record of leading large-scale AI projects , defining architecture, and managing cross-functional teams.
Job Title: Associate Director
Role: AI Architect
Experience: 12+ Years
About the Role:
We are seeking a Principal AI Engineer / AI Architect with extensive experience in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , and Agentic AI systems . This role requires strategic leadership , architectural design , and delivery of large-scale AI projects . You will define technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives.
Key Responsibilities:
Lead and architect enterprise-scale AI solutions leveraging LLMs, multimodal models, and advanced GenAI techniques.
Design and oversee RAG pipelines and Agentic AI frameworks for complex workflows.
Define AI architecture standards , scalability strategies, and integration patterns with cloud services.
Drive effort estimation , resource planning, and delivery timelines for large-scale AI projects.
Collaborate with senior stakeholders to propose AI-driven solutions and influence technology strategy.
Ensure compliance with security, governance, and ethical AI principles .
Oversee model deployment, model cost estimation in production environments and ensure robust monitoring.
Lead MVP development for rapid prototyping and proof-of-concept initiatives.
Mentor and guide engineering teams, fostering innovation and best practices.
Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
Generative AI: Proven experience in LLM fine-tuning, prompt engineering, and production deployment.
RAG & Agentic AI: Advanced knowledge of embeddings, vector databases (FAISS, Pinecone), and agent orchestration frameworks (LangChain, AutoGen).
Traditional ML & Deep Learning: Strong foundation in ML algorithms and deep learning architectures (CNNs, RNNs, Transformers).
Architecture & Leadership: Ability to design scalable AI architectures , manage large teams, and deliver enterprise projects.
Cloud Expertise: Strong understanding of cloud services (AWS, Azure, GCP), including compute, storage, networking, and AI-specific offerings.
MVP Development: Experience creating proof-of-concepts and MVPs for rapid prototyping and stakeholder validation.
Production Deployment: Should have proven capability to production
Excellent communication and stakeholder management skills.
Preferred Skills:
Experience with MLOps , CI/CD for AI, and multi-cloud deployments .
Familiarity with cost optimization , security best practices , and disaster recovery strategies .
Exposure to multi-modal AI , agent orchestration , and AI governance frameworks
Hands-on experience deploying AI models in production environments with monitoring and scaling strategies.
Cost Estimation: Exposure to estimating LLM model costs prior to deployment , including compute, storage, and inference optimization.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
12+ years of experience in AI/ML development, with at least 5+ years in Generative AI and advanced AI systems .
Proven track record of leading large-scale AI projects , defining architecture, and managing cross-functional teams.
Job Title: Associate Director
Role: AI Architect
Experience: 12+ Years
About the Role:
We are seeking a Principal AI Engineer / AI Architect with extensive experience in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , and Agentic AI systems . This role requires strategic leadership , architectural design , and delivery of large-scale AI projects . You will define technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives.
Key Responsibilities:
Lead and architect enterprise-scale AI solutions leveraging LLMs, multimodal models, and advanced GenAI techniques.
Design and oversee RAG pipelines and Agentic AI frameworks for complex workflows.
Define AI architecture standards , scalability strategies, and integration patterns with cloud services.
Drive effort estimation , resource planning, and delivery timelines for large-scale AI projects.
Collaborate with senior stakeholders to propose AI-driven solutions and influence technology strategy.
Ensure compliance with security, governance, and ethical AI principles .
Oversee model deployment, model cost estimation in production environments and ensure robust monitoring.
Lead MVP development for rapid prototyping and proof-of-concept initiatives.
Mentor and guide engineering teams, fostering innovation and best practices.
Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
Generative AI: Proven experience in LLM fine-tuning, prompt engineering, and production deployment.
RAG & Agentic AI: Advanced knowledge of embeddings, vector databases (FAISS, Pinecone), and agent orchestration frameworks (LangChain, AutoGen).
Traditional ML & Deep Learning: Strong foundation in ML algorithms and deep learning architectures (CNNs, RNNs, Transformers).
Architecture & Leadership: Ability to design scalable AI architectures , manage large teams, and deliver enterprise projects.
Cloud Expertise: Strong understanding of cloud services (AWS, Azure, GCP), including compute, storage, networking, and AI-specific offerings.
MVP Development: Experience creating proof-of-concepts and MVPs for rapid prototyping and stakeholder validation.
Production Deployment: Should have proven capability to production
Excellent communication and stakeholder management skills.
Preferred Skills:
Experience with MLOps , CI/CD for AI, and multi-cloud deployments .
Familiarity with cost optimization , security best practices , and disaster recovery strategies .
Exposure to multi-modal AI , agent orchestration , and AI governance frameworks
Hands-on experience deploying AI models in production environments with monitoring and scaling strategies.
Cost Estimation: Exposure to estimating LLM model costs prior to deployment , including compute, storage, and inference optimization.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
12+ years of experience in AI/ML development, with at least 5+ years in Generative AI and advanced AI systems .
Proven track record of leading large-scale AI projects , defining architecture, and managing cross-functional teams.