Gen AI Architect

Role & responsibilities

The Generative AI Architect is a strategic technical leader responsible for designing, implementing, and managing advanced generative AI solutions across Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS). This role combines deep expertise in generative AI technologies, multi-cloud architecture, and modern software engineering practices to deliver scalable, secure, and innovative AI products. The architect leads cross-functional teams, drives technical vision, and ensures alignment between business objectives and AI initiatives

Preferred candidate profile

• 10+ years of IT experience, with 2+ years in generative AI, LLMs, or related AI/ML technologies.
• Advanced proficiency in Python, with ability to build modular APIs, pipelines, and orchestration frameworks.
• Hands-on expertise in at least one generative AI framework: LangChain, LangGraph, Google ADK, Azure AI Studio or AWS Bedrock and understanding of others.
• Experience integrating LLMs via APIs (OpenAI, Gemini, Hugging Face, etc.).
• Strong knowledge of RAG, embeddings, and vector databases.
• Familiarity with PEFT, LoRA, or prompt fine-tuning approaches.
• Cloud expertise in at least one hyperscaler (GCP, Azure, or AWS), with working knowledge of:
• GCP: Vertex AI, Document AI, BigQuery, AlloyDB, Cloud Run, IAM
• Azure: OpenAI Service, Cognitive Search, Azure ML, Azure Functions, Azure Identity
• AWS: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, IAM
• Understanding of Docker/Kubernetes, CI/CD, and Git-based version control.
• Knowledge of REST APIs, JSON, and frameworks like FastAPI or Flask.
• Familiarity with data governance, security, and AI ethics.
• Strong problem-solving, project management, and communication skills.
• Ability to drive innovation and influence strategic decisions.