We are looking for a Senior AI/GenAI Engineer with strong hands-on experience building and deploying production-grade AI solutions on Azure . This is not a data engineering role. This role is responsible for designing end-to-end AI architectures, leading technical decisions, and translating business needs into scalable, reliable, and secure GenAI systems.
You will work closely with cross-functional teams to deliver AI-powered solutions (copilots, AI agents, RAG pipelines) that support both internal operations and client-facing services.
Responsibilities
- Design, build, and deploy production-grade GenAI solutions (AI agents, copilots, RAG pipelines) with a focus on scalability, reliability, and performance
- Own end-to-end architecture of AI systems on Azure, including integration with enterprise data platforms and backend services
- Lead the development of LLM-powered applications using Azure-native services and modern orchestration frameworks
- Implement LLMOps practices , including monitoring, logging, evaluation, prompt/version management, and cost optimization
- Translate business requirements into technical AI solutions and define scalable implementation strategies
- Ensure security, governance, and compliance across all AI solutions
- Optimize AI systems for latency, cost, and accuracy in production environments
- Provide technical leadership , mentor engineers, and drive best practices in system design and code quality
Requirements
- Proven experience as a Senior or Lead Engineer delivering production-grade AI/ML or GenAI solutions
- Strong hands-on expertise in Azure , including designing and deploying end-to-end AI architectures
- Experience with Azure AI Foundry , Azure OpenAI , and enterprise AI service integration
- Solid experience building AI agents using Microsoft Agent Framework (or similar frameworks)
- Strong Python experience building AI applications, APIs, and LLM-based services (not only data pipelines)
- Strong experience with RAG architectures , prompt engineering, and LLM orchestration
- Experience with Databricks, Azure Data Factory, and SQL for data-driven AI solutions
- Hands-on experience with LLMOps / MLOps practices (monitoring, evaluation, versioning, deployment pipelines)
- Strong understanding of system design, scalability, and distributed systems
- Proven ability to deliver measurable impact in production environments (e.g., automation, cost savings, performance improvements)
- Strong communication skills with the ability to work with both technical and non-technical stakeholders
- Experience leading technical initiatives and mentoring engineers in a delivery-focused environment
Benefits
At Devsu , we believe in creating an environment where you can thrive both personally and professionally. By