Generative AI Architect

Key Responsibilities:

• Design end-to-end architectures for Generative AI solutions (text, image, video, code generation).
• Evaluate and integrate foundation models like OpenAI GPT, Google Gemini, Mistral, LLaMA, Claude, etc.
• Build scalable GenAI pipelines for training, fine-tuning, prompt engineering, and inference.
• Collaborate with data scientists, ML engineers, and software developers to operationalize AI models.
• Lead PoCs and MVPs in collaboration with business stakeholders.
• Implement RAG (Retrieval Augmented Generation) pipelines for context-aware applications.
• Define best practices for model deployment (API, containerization, CI/CD).
• Ensure responsible AI compliance and model monitoring in production.
• Optimize performance and cost of GenAI workloads on cloud platforms (AWS, Azure, GCP).

Required Skills:

• Strong experience with GenAI models (GPT, BERT, LLaMA, Stable Diffusion, DALL·E, etc.)
• Proficient in Python, PyTorch, TensorFlow, LangChain, Transformers (Hugging Face)
• Deep understanding of prompt engineering, model fine-tuning (LoRA, PEFT)
• Experience with RAG pipelines, vector databases (Pinecone, FAISS, Weaviate, Chroma)
• Cloud-native development on AWS, Azure, or GCP (SageMaker, Vertex AI, Azure ML)
• Hands-on with APIs, microservices, and orchestration tools (Docker, Kubernetes, Airflow)
• Familiar with data engineering workflows, MLOps, and security best practices.

Nice to Have:

• Experience with multimodal models (e.g., video/audio + text)
• Exposure to enterprise LLMs and model hosting platforms (Anthropic, Cohere, Mistral)
• Understanding of ethical AI, bias detection, and explainability
• Prior experience in GenAI for specific domains (Healthcare, Finance, Retail, etc.)

Educational Background:

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field
• Certifications in cloud architecture or AI/ML preferred

Soft Skills:

• Strong problem-solving and architectural thinking
• Ability to communicate complex concepts to non-technical stakeholders
• Passionate about staying ahead in the AI/ML space