AI Engineer - AM

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

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

Programming: Expert-level proficiency in Python and AI/ML libraries (Py. Torch, Tensor. Flow, 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 (Lang.

Chain, Auto. Gen). 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 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

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

Programming: Expert-level proficiency in Python and AI/ML libraries (Py. Torch, Tensor. Flow, 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 (Lang.

Chain, Auto. Gen). 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 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

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

Programming: Expert-level proficiency in Python and AI/ML libraries (Py. Torch, Tensor. Flow, 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 (Lang.

Chain, Auto. Gen). 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