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AI Architect

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Onsite

AI Architect

Steerlean

AI Architect

Skills

Google Cloud PlatformDockerPythonData SciencePyTorchTensorFlowMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingFastAPIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Gurugram, Haryana, India

Work mode:

Onsite

Published on:

13 August 2026

What they need


Description :

We are seeking an experienced AI Architect to lead the design, development, and deployment of large-scale AI solutions.

The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices.

Key Responsibilities :

AI Solution Design & Implementation :

  • Architect end-to-end AI systems leveraging large language models and generative AI technologies

  • Evaluate and integrate LLM APIs from leading providers (OpenAI, Anthropic Claude, Google Gemini, etc.)

  • Establish best practices for prompt engineering, model selection, and AI system optimization

Model Development & Fine-tuning :

  • Fine-tune open-source models (Llama, Mistral, etc.) for specific business use cases

Infrastructure & Deployment :

  • Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes)

  • Build robust, scalable APIs using FastAPI and similar frameworks

  • Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment

Minimum Requirement :

  • At least 5+ years of experience in machine learning engineering or data science

  • At least 1+ years of hands-on experience building, deploying, and managing generative AI models in production

  • Proven track record of delivering large-scale ML solutions

Technical Skills :

  • Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.)

  • Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.)

  • Strong proficiency in FastAPI, Docker, and Kubernetes

  • Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)

  • Proficiency in Python and modern software development practices

  • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services

Core Competencies :

  • Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques

  • Experience with MLOps tools and practices (model versioning, monitoring, CI/CD)

  • Ability to translate complex business requirements into technical solutions

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