Gen AI Engineer - AD 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: Robust 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: Robust 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.

Experience Level Senior Level

📌 Associate Director - AI Architect (Pune)
🏢 KPMG India Services
📍 Pune