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