AI Engineer - AM
Bengaluru · Senior
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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
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
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
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