You will be taken to KPMG’s own careers page to apply. Job ID 30048531.
Job description
Description We are seeking a AI Engineer / AI Architect with extensive experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Agentic AI systems. This role requires high technical acumen, architectural design, and delivery of large-scale AI projects. You will influence technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives. Responsibilities 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 and be able to implement them from scratch.
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 AI & engineering teams, fostering innovation and best practices.
Qualifications Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face) and FastAPI.
Should know the basics of frontend development
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.
Excellent communication and stakeholder management skills.
Additional 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.
5+ years of experience in AI/ML development, with at least 3+ years in Generative AI and advanced Agentic AI systems.
Proven track record of implementing large-scale AI projects
Responsibilities
Description We are seeking a AI Engineer / AI Architect with extensive experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Agentic AI systems. This role requires high technical acumen, architectural design, and delivery of large-scale AI projects. You will influence technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives. Responsibilities 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 and be able to implement them from scratch.
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 AI & engineering teams, fostering innovation and best practices.
Qualifications Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face) and FastAPI.
Should know the basics of frontend development
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.
Excellent communication and stakeholder management skills.
Additional 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.
5+ years of experience in AI/ML development, with at least 3+ years in Generative AI and advanced Agentic AI systems.
Proven track record of implementing large-scale AI projects
Requirements
Description We are seeking a AI Engineer / AI Architect with extensive experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Agentic AI systems. This role requires high technical acumen, architectural design, and delivery of large-scale AI projects. You will influence technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives. Responsibilities 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 and be able to implement them from scratch.
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 AI & engineering teams, fostering innovation and best practices.
Qualifications Required Skills:
Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face) and FastAPI.
Should know the basics of frontend development
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.
Excellent communication and stakeholder management skills.
Additional 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.
5+ years of experience in AI/ML development, with at least 3+ years in Generative AI and advanced Agentic AI systems.
Proven track record of implementing large-scale AI projects
