AI Architect

We are seeking an experienced AI Architect to design and implement scalable, secure, and production-ready AI solutions. The ideal candidate will have strong experience in Generative AI, Machine Learning, Cloud Platforms, LLMs, and AI architecture, along with the ability to translate business requirements into robust technical solutions.

The AI Architect will work closely with business stakeholders, data scientists, software engineers, cloud engineers, and product teams to define AI strategies, architecture patterns, and end-to-end implementation solutions.

Key Responsibilities

• Design and lead end-to-end AI/ML and Generative AI architectures for enterprise applications.
• Define AI solution architecture, technology strategy, integration patterns, and implementation roadmaps.
• Design solutions using Large Language Models (LLMs), Generative AI, RAG, embeddings, vector databases, and AI agents.
• Evaluate and select appropriate AI models, frameworks, platforms, and tools based on business and technical requirements.
• Develop scalable AI solutions using cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines and enterprise knowledge solutions.
• Integrate AI capabilities with existing enterprise applications through REST APIs, microservices, and event-driven architectures.
• Establish best practices for AI security, governance, privacy, responsible AI, and model lifecycle management.
• Collaborate with data engineering and ML engineering teams on data pipelines, model development, deployment, and monitoring.
• Provide technical leadership and mentor engineering teams.
• Conduct architecture reviews and ensure solutions meet scalability, performance, reliability, and security standards.
• Create architecture diagrams, technical documentation, design specifications, and implementation guidelines.
• Stay current with emerging technologies in Generative AI, LLMs, Agentic AI, Machine Learning, and cloud AI services.

Required Technical Skills

• 8+ years of experience in software, data, cloud, or AI/ML engineering, with significant experience in AI architecture.
• Strong hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, prompt engineering, vector databases, and AI agents.
• Strong programming experience with Python and/or Java.
• Experience with AI/ML frameworks such as PyTorch, TensorFlow, LangChain, or LlamaIndex.
• Experience with cloud AI services such as Azure OpenAI, AWS Bedrock, Amazon SageMaker, or Google Vertex AI.
• Strong understanding of REST APIs, microservices, distributed systems, and cloud-native architectures.
• Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, Milvus, or pgvector.
• Experience with relational and NoSQL databases.
• Strong knowledge of Docker, Kubernetes, CI/CD, Git, and DevOps practices.
• Experience designing secure and scalable enterprise AI applications.
• Understanding of MLOps/LLMOps, model deployment, monitoring, evaluation, and lifecycle management.