Sonata Software - Generative AI Architect

Job Description : Gen AI Architect

We are seeking an experienced Gen AI Architect to lead the design, development, and deployment of next-generation AI-driven solutions across our product ecosystem. This role is ideal for someone who combines deep technical expertise with strong architectural thinking, hands-on development capability, and a passion for building scalable, production-grade AI systems. You will work closely with engineering, product, and cloud teams to translate business needs into robust Gen AI architectures leveraging modern frameworks and Azure services.

Responsibilities :

- Architect, design, and implement end-to-end Gen AI solutions using LLMs, vector databases, and agentic workflows.

- Build intelligent applications using .NET, Azure OpenAI, LangChain, and Agentic AI frameworks.

- Develop reusable AI components, prompt templates, pipelines, and orchestration layers.

- Design secure, scalable, and compliant AI architectures for enterprise environments.

- Integrate LLM-powered features into existing products, including reasoning agents, RAG systems, copilots, and automation flows.

- Build and manage cloud-native AI services using Azure Functions, Azure Cognitive Search, and related Azure services.

- Lead deployment, monitoring, and performance optimization of AI models in production.

- Collaborate with cross-functional teams to evaluate use cases, refine requirements, and ensure successful implementation.

- Establish best practices for AI development, MLOps, DevOps workflows, and governance.

- Stay ahead of Gen AI advancements and drive adoption of emerging technologies.

Requirements :

- 6- 12 years of experience in software architecture or full-stack engineering, with at least 2- 4 years in Gen AI / LLM-based systems.

- Strong proficiency in .NET and modern backend development.

- Hands-on experience with LLMs, LangChain, Agentic AI frameworks, and vector stores.

- Deep experience with Azure OpenAI, Azure Functions, Azure DevOps, and cloud deployments.

- Solid understanding of AI security, scaling patterns, prompt engineering, and evaluation techniques.

- Proven ability to design high-availability, production-grade AI architectures.

- Excellent communication, problem-solving, and technical leadership skills.