AI Architect (Product base experience)

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

Design scalable, production-ready AI applications that meet business objectives and performance requirements

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

Implement custom training pipelines and evaluation frameworks

Optimize model performance, latency, and cost for production environments

Stay current with latest model architectures and fine-tuning techniques

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

Ensure high availability, security, and performance of AI systems in production

Business & Technical Leadership

Collaborate with stakeholders to understand business problems and translate them into technical requirements

Provide technical guidance and mentorship to development teams

Conduct feasibility assessments and technical due diligence for AI initiatives

Create technical documentation, architectural diagrams, and implementation roadmaps

Required Qualifications

Experience

7+ years of experience in machine learning engineering or data science

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

Strong problem-solving skills and architectural thinking

Preferred Qualifications

Experience with vector databases and retrieval-augmented generation (RAG) systems

Knowledge of distributed training and model parallelization techniques

Experience with model quantization and optimization for edge deployment

Familiarity with AI safety, alignment, and responsible AI practices

Experience in specific domains (finance, healthcare, legal, etc.)

Advanced degree in Computer Science, AI/ML, or related field