AI Architect

We are looking for an experienced AI Architect to define and lead the architecture of scalable, secure, and production-ready AI/ML and Generative AI solutions. The candidate should combine strong AI/ML knowledge with enterprise architecture, cloud, data, software engineering, security, and integration experience, and be capable of converting business requirements into practical AI architectures.

Key Responsibilities

• Define end-to-end AI/ML and GenAI architecture for enterprise solutions.
• Translate business requirements into scalable AI solution architectures and technical designs.
• Select appropriate ML, Deep Learning, LLM, RAG, Agentic AI, optimization, or hybrid approaches.
• Design AI platforms covering data ingestion, processing, model development, model serving, APIs, applications, monitoring, and governance.
• Define architectures for LLMs, RAG, vector databases, AI agents, knowledge bases, and AI orchestration. Design cloud-native AI solutions across Azure, AWS, or GCP.
• Define integration patterns between AI services and enterprise applications, APIs, databases, data platforms, and external systems.
• Establish standards for MLOps, LLMOps, model lifecycle management, monitoring, evaluation, and CI/CD.
• Address AI security, privacy, governance, responsible AI, access control, data protection, and compliance requirements.
• Evaluate AI technologies, models, frameworks, and platforms and make architecture recommendations.
• Lead PoCs and architecture assessments and guide engineering teams through implementation.
• Review technical designs, identify architecture risks, and provide technical direction to AI/ML and software engineering teams.

Must-Have Skills

• 10+ years in software/technology architecture, AI/ML, or related engineering roles.
• Strong understanding of Machine Learning, Deep Learning, Generative AI and LLMs. Strong hands-on knowledge of Python and AI/ML frameworks. Strong experience with LLM, RAG, embeddings, vector databases, agents and AI orchestration. Strong understanding of data architecture and data pipelines. Experience designing cloud-native and scalable distributed systems. Strong knowledge of APIs, microservices, containers, Docker and Kubernetes. Experience with MLOps/LLMOps, model deployment and monitoring. Strong understanding of security, governance, scalability, performance, availability, and cost optimization. Ability to communicate architecture and technical decisions effectively to business, product, engineering, and senior management.

Good to Have

• Azure AI / AWS AI / Google Cloud AI experience. Azure OpenAI or equivalent enterprise LLM platforms. Experience with Hugging Face, LangChain, LlamaIndex, MLflow or equivalent. Experience with GPU architecture and model optimization. Experience with enterprise data platforms, Data Lakes, Lakehouse, Databricks, Microsoft Fabric, etc. Experience with Computer Vision, NLP, forecasting, optimization, or AI agents. Experience defining enterprise AI governance and responsible AI frameworks.

What We Are Looking For

An architect who can go beyond selecting AI technologies and define how AI fits into the overall enterprise architecture — covering data, models, applications, infrastructure, integration, security, governance, scalability, operations, and cost.

Work Location: In person