Steerlean
AI Architect
Skills
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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