- Work model
- Office
- Experience
- 5+ years
- Employment
- Not specified
- Compensation
- Not disclosed
- Technology signal
- 29 tags
Technology context
29Parsed from the vacancy text; ordered by relevance to this role.
Node.jsAI AgentsAILLMReact.jsFull StackAI-Assisted DevelopmentC#DatabasesMachine Learning.NETAzurePythonRAGKubernetesCloudNLPDevOpsDockerMicroservicesPostgreSQLDatabricksRESTCI/CDGraphQLAI Solution EngineeringAzure Kubernetes ServiceGitHubMicrosoft Foundry
Full listing
Role description
We are seeking a Lead/Senior Software Engineer specializing in AI Solution Engineering to design, build, and deploy full-stack LLM-powered AI applications while driving best practices in cloud architecture, coding standards, and responsible AI delivery across enterprise systems.
Responsibilities
- Build full-stack LLM-powered AI applications using Azure (prompt engineering, grounding, RAG) or vector databases
- Develop APIs/microservices with Python, .NET, or Node and integrate them with UIs and enterprise systems
- Drive agentic AI development using Azure AI Foundry and Copilot Studio
- Implement CI/CD pipelines with GitHub Actions or Azure DevOps and manage cloud deployments across AKS, App Service, and Functions
- Build data and feature pipelines using Azure Data Factory, Synapse, or Databricks and manage embeddings and prompt versioning
- Deploy models into production and maintain them over time
- Adhere to coding standards and AI principles by conducting regular health checks, audits, and code reviews to ensure clean, maintainable, production-level code across project teams
Requirements
- 6-14 years of overall IT experience
- Strong coding skills in Python, C#, and REST/GraphQL APIs, along with experience in testing and code reviews
- Hands-on expertise in the Azure AI stack, including Azure OpenAI, Azure AI Foundry, and Azure Cognitive Services
- Familiarity with Azure AI Search, NLP, and Azure ML, along with vector databases such as AI Search vector index, Cosmos DB, or PostgreSQL
- Experience in agentic development using the Azure AI stack
- Proficiency in CI/CD with GitHub, branching strategies, and coding standards such as linters, formatters, and PEP8, along with GitHub Actions pipelines
- Skills in containerization with Docker and deployment to AKS, App Service, or Functions
- Knowledge of secrets management via Key Vault and Managed Identity, along with RBAC and network security basics
- Understanding of Responsible AI, privacy, and data security in enterprise settings
Nice to have
- Experience with GitHub Copilot and Microsoft Copilot Studio (Power Platform)
- Familiarity with PromptFlow, MLflow, Databricks, and Streamlit or React
- Background in MLOps and/or LLMOps practices
- Azure certifications (AI-102, AZ-204)
- Experience working with one of the big cloud environments (e.g. Azure)
- Knowledge of RAG patterns, prompt design, tool/function calling, embeddings, retrieval, and caching
- Preferred experience working with Asset projects