Job description

Job Requirements We are seeking a visionary and hands-on AI Solutions Architect to lead the design and implementation of a modular, scalable, and high-performance LLM-based Engineering Assistant on the Azure platform. This role is ideal for someone who thrives at the intersection of AI, cloud architecture, and engineering workflows, and can translate business needs into robust technical solutions. Key Responsibilities: Architecture & Design • Design end-to-end architecture for an LLM-powered assistant using Azure services (e.g., Azure OpenAI, Azure Data Factory, Azure AI Search, Blob Storage, PostgreSQL). • Define modular components for data ingestion, preprocessing, model orchestration, retrieval-augmented generation (RAG), and agentic workflows. • Ensure scalability, security, and maintainability of the system. Resource Planning & Strategy • Identify and recommend key Azure resources, third-party tools, and frameworks required for implementation. • Evaluate trade-offs between performance, cost, and complexity. Implementation Leadership • Collaborate with engineering and data teams to implement the architecture. • Guide the development of pipelines for structured and unstructured data integration. • Oversee deployment, monitoring, and optimization of the assistant. Team Enablement & Communication • Communicate architectural vision clearly to cross-functional teams. • Create documentation, diagrams, and onboarding materials. • Mentor developers and engineers on best practices in AI and cloud-native development. Work Experience Required Qualifications: • Proven experience architecting AI/ML or LLM-based applications on Azure. • Strong understanding of Azure services: OpenAI, Data Factory, AI Search, Blob Storage, PostgreSQL, Functions, etc. • Experience with agentic workflows, RAG, vector databases, and orchestration frameworks. • Background in engineering domains (mechanical, electrical, systems) is a strong plus. • Excellent communication and leadership skills Preferred Skills: • Familiarity with Gas Turbine domain • Experience with MLOps and CI/CD pipelines. • Knowledge of semantic search, embeddings, and knowledge graphs. • Ability to work in agile environments and manage multiple stakeholders.

Requirements