Hire Developers
Hire Azure AI Developer
Production AI features — secure, measurable, and maintainable.
Add a specialist who can build AI features on Azure with the full production lifecycle: architecture, safety, evaluation, monitoring, and cost governance. Ideal when AI needs to move beyond demos.
RAG & Knowledge Systems
Ingestion, embeddings, retrieval, and grounding to reduce hallucinations.
Safety & Governance
Private access patterns, content filters, and data handling policies.
Quality & Cost Visibility
Evaluation, telemetry, and token cost tracking for long-term control.
Engagement Models
Choose the engagement model based on speed, scope, and risk profile.
AI Feature Sprint
Implement one AI workflow end-to-end with evaluation and monitoring.
- Chatbots
- Summarization
- Extraction
AI Platform Foundations
Build the secure foundation: networking, identity, governance, and telemetry.
- Enterprise AI
- Multiple teams
- Compliance requirements
Continuous Improvement
Improve quality over time with evaluation, analytics, and prompt iterations.
- Scaling adoption
- Reducing hallucinations
- Cost optimization
Typical Skills & Responsibilities
An Azure AI developer owns both the AI layer and the production system around it.
Azure AI
RAG & Data
Production
How AI Delivery Works
A structured approach that makes AI quality measurable and supportable.
Define Success
Use cases, success metrics, and safety requirements.
Design
Architecture, data flow, governance controls, and evaluation plan.
Build & Evaluate
Implement and run evaluation against real questions and samples.
Deploy & Improve
Monitoring, analytics, and an improvement backlog over time.
AI Hiring Questions
Grounding (RAG), structured outputs, safety guardrails, and evaluation regressions — plus fallback behavior when confidence is low.
Ship AI Features With Confidence
Tell us your AI use case and constraints. We’ll propose an Azure AI developer engagement with clear milestones and measurable outcomes.