Senior Software Engineer - AI Gateway & Agentic AI Solutions

Top 5 Responsibilities Architect and implement the AI Gateway. Design and build an Azure-native LLM gateway in C# providing unified ingress across multiple model providers (Azure OpenAI, Azure AI Foundry models, and others) - covering intelligent routing, fallback/load balancing, rate limiting and token-quota enforcement, semantic caching, and centralized API key/secret management. Reference the LiteLLM feature set as the functional bar to hit. Build the observability and governance layer. Implement request/response tracing, prompt/completion logging, token and cost metering, and latency dashboards - the Langfuse-equivalent half of the stack - using Azure Monitor, Application Insights, OpenTelemetry, and APIM's native LLM logging/token-metric policies (or a self-hosted Langfuse instance where warranted). Deliver multiple Agentic AI PoC scenarios. Using C# and the Microsoft Agent Framework, build a portfolio of distinct agentic patterns (single-agent tool use, multi-agent orchestration, human-in-the-loop workflows, RAG-grounded agents) mapped to real client business use cases - not one deep PoC, but several breadth-covering scenarios that demonstrate different capabilities. Own technical delivery on client engagements end-to-end. Run architecture proposals, hands-on build, live demos, and production-readiness assessments directly with client technical stakeholders; translate ambiguous business asks into scoped, demoable agentic scenarios. Package the work as reusable engineering assets. Turn the gateway and agent scenarios into templates, SDKs, or IaaC that can be re-deployed across environments rather than rebuilt from scratch each time - even though this is a client-facing role, the artifacts should outlive any single client environment.