KPMG IndiaVerified listingGen AI Engineer - AD
PuneOn-siteDirector
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The post's words + ASAI's dataOn-site in Pune.
OK with that?Director level, usually 12-15 years.
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Reposted. This role was posted earlier, closed, and has now reopened - the company is accepting candidates again.
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The job post
1257 words · from KPMG India's careers siteJob 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.
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