Senior .NET Developer

• Lead design and implementation of cloud-native, event-driven platforms that integrate many independent systems into a unified operational ecosystem.
• Architect Azure Durable Functions workflows using Service Bus and Event Grid to orchestrate and process high daily event volumes with reliability, retries, and recovery.
• Build C# / .NET backend services that generate and distribute structured metadata and events to downstream consumers under tight availability SLAs, including near-real-time propagation targets.
• Design scalable, fault-tolerant microservice-style components that can be extended without rewriting the platform.
• Integrate internal and third-party systems through REST and GraphQL; use Azure API Management as the gateway.
• Design and implement AI product architecture on Azure: model-serving and inference paths, retrieval / grounding pipelines, prompt-and-tool orchestration, and secure service interfaces for LLM interaction.
• Build MCP-style and function-calling interfaces so agents and LLMs can invoke platform APIs safely (auth, scoped tools, timeouts, audit).
• Optimize AI workloads for production: token and compute cost, latency budgets, rate limits, caching, fallback models, and evaluation / tracing of model calls.
• Implement durable storage with Blob Storage and Table Storage for event-driven exchange, recovery, embeddings or document corpora, and audit of AI and integration traffic.
• Establish observability across application and AI paths: structured logging, distributed tracing, prompt/tool telemetry where appropriate, and alerting in Application Insights.
• Influence architecture, raise code quality, and mentor engineers on backend and AI-integration patterns.
• Translate stakeholder requirements into production-ready designs and incremental delivery.

• Professional software engineering experience as a senior or lead engineer on Azure backend platforms.
• Strong C# / .NET, including .NET 6/8+ and ASP.NET Core.
• Hands-on Azure: Functions, Durable Functions, Service Bus, Event Grid, Blob Storage, Table Storage, API Management, App Services, Key Vault, and App Configuration.
• Proven event-driven and distributed-systems design (orchestration, pub/sub, idempotency, failure handling).
• Experience optimizing architecture for AI products in production: integrating LLMs or Azure OpenAI, designing tool/API access for models, and addressing cost, latency, reliability, and security of model use.
• REST and GraphQL integration experience; comfort with API gateways.
• SQL Server and data access via EF Core or equivalent.
• Observability in production (Application Insights or similar), including visibility into downstream AI calls when those are part of the service path.
• Azure DevOps (or equivalent) with YAML CI/CD.
• Ability to lead technical decisions and work directly with product and business stakeholders., * Azure OpenAI, Amazon Bedrock, or equivalent LLM platforms used behind APIM or other governed gateways.
• MCP servers, tool-calling, function-calling, or agent-orchestration patterns in production or serious pilot systems.
• Retrieval-augmented generation (RAG): document ingestion, chunking, embeddings, vector or hybrid search, grounding and citation.
• AI evaluation, red-teaming, or quality gates (offline eval sets, online traces, hallucination / tool-failure handling).
• SCTE-224 or other broadcast / media metadata standards.
• Clean Architecture, DDD, or behavior-driven design in production services.
• Python, JavaScript, or PowerShell for automation, evaluation harnesses, and integration.
• AWS (EC2, Lambda) in addition to Azure.
• Multi-tenant or large-scale enterprise backends.
• B.S. in Computer Science or equivalent experience.

Core skills

C#, .NET 8+, ASP.NET Core, EF Core, SQL, Azure Functions / Durable Functions, Service Bus, Event Grid, APIM, Blob/Table Storage, Key Vault, Application Insights, Azure DevOps YAML pipelines, REST, GraphQL, Azure OpenAI / LLM integration, MCP and tool-calling interfaces, RAG / retrieval pipelines, event-driven architecture, microservices, AI cost and latency optimization.

Pay: $190,000.00 - $220,000.00 per year

Application Question(s):

• Are you willing to obtain a Public Trust Clearance?
• Do you have AI Development experience?