Azure AI Developer and Architect
GTECH LLC · San Francisco, CA · Yesterday
On-siteEngineeringFull-time
needs a senior, hands-on Azure AI Developer / Architect to lead customer AI application delivery, rapid prototypes and MVPs. The role sits in a growing Microsoft AI practice and will work across Azure AI Foundry, agentic workflows, RAG patterns, document intelligence, enterprise integrations and AI engineering guardrails. This is not a low-code Copilot Studio position and not a detached enterprise architecture role. The successful candidate must be a genuine builder who can design, code and guide delivery. They will help clients convert broad AI interest into practical, governed use cases, build applications that integrate with systems such as SAP and Salesforce, and ensure work is developed securely within the customer s Azure environment. The preferred foundation is .NET/C# application development combined with Python and modern engineering practice. Candidates should understand LLMs, tokens, models, model routing, document processing, retrieval/search, RAG, agentic workflows, MCP, Git, repositories, branching, release discipline and secure enterprise deployment. They do not need to be a fully formed practice leader, but must have the technical credibility and learning agility to grow into delivery leadership. The role is remote, customer-facing and requires Pacific Time coverage. Novulis is open to FTE or contract-to-hire, with a preference for retaining and developing internal expertise. Must have Hands-on AI application development experience.Azure AI Foundry and adjacent Azure AI service exposure.RAG, LLM, retrieval/search and agentic-workflow delivery experience.Strong .NET/C# and/or Python engineering background.Git, branching, release and development governance discipline.Enterprise systems integration and customer-facing delivery capability. Screen out Low-code-only Copilot Studio candidates.Prompt engineers without software engineering depth.AI architects who cannot code or describe a production delivery lifecycle.Candidates focused only on public AI APIs without enterprise security/governance understanding.