AI / ML / GenAI - Architect

Key Responsibilities

• Design, develop, and deploy AI/ML architectures for enterprise-scale applications.
• Lead Generative AI and NLP initiatives, including working with LLMs, embeddings, transformers, and text analytics.
• Collaborate with business and engineering teams to translate requirements into AI-driven solutions.
• Oversee the entire ML lifecycle: data preprocessing, feature engineering, model development, evaluation, deployment, and monitoring.
• Drive MLOps best practices, ensuring scalable, reliable, and maintainable AI/ML pipelines.
• Evaluate and integrate open-source frameworks, APIs, and tools like LangChain, Hugging Face, OpenAI, etc.
• Mentor technical teams and provide thought leadership on AI/ML strategy, architecture, and best practices.
• Ensure AI solutions comply with ethical standards, data privacy, and security policies.
  

Technical Skills

• Programming: Advanced proficiency in Python and related AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, spaCy.
• AI/ML Expertise: Experience with supervised, unsupervised, and reinforcement learning algorithms.
• GenAI & NLP: Hands-on experience with LLMs, prompt engineering, embeddings, and NLP pipelines.
• Data & Cloud: Expertise in data preprocessing, model optimization, and deployment on AWS, Azure, or GCP