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 workplace.
Responsibilities
Top 5 Required Skills / Background
• Deep C#/.NET engineering background (12-15+ years). Production-grade API/service development, async patterns, dependency injection, testing discipline, and comf
📌 Senior Software Engineer (Gurugram)
🏢 EXL
📍 Gurugram