Full Stack Developer - AI Integration
Direct Hire
Washington DC – Hybrid role (2-3 days onsite) About the Role
Our client is expanding their AI offerings and needs a full ‐ stack developer who can design, build, and integrate AI components into customers' existing platforms. You'll work across the stack—C#/.NET services, modern JavaScript front ends, and data integrations—while delivering production ‐ grade AI features, including customized, agentic AI workflows that call tools, route tasks, and operate safely at scale. What You'll Do
- Design, build, and integrate AI features into customer platforms (web apps, CRMs, ERPs, support systems, custom tools)
- Develop and maintain C#/.NET APIs and services that orchestrate LLMs, tools, and data sources
- Implement agentic AI patterns (tool/function calling, routing/planning, memory, multi ‐ step workflows) for real business use cases
- Build front-end experiences in React and/or Angular for prompt UIs, chat/agent consoles, and admin tooling
- Ship robust data integrations (REST/GraphQL/webhooks), including ETL/ELT for RAG pipelines and system-to-system sync
- Implement secure authentication/authorization, audit trails, rate limiting, cost controls, and observability
- Produce clear documentation, deployment guides, and client ‐ facing enablement; partner with delivery and customer teams
- Professional full ‐ stack experience building production systems with C#/.NET (5+ years preferred)
- Recent, paid professional experience delivering agentic AI solutions (not side projects), e.g.:
- Tool/function calling, orchestration, task planning, retries, grounding, and memory
- Integrations with LLM APIs (e.g., Azure OpenAI/OpenAI/Anthropic/Vertex) in production
- Hands-on front-end development with modern JS libraries (React and/or Angular)
- Strong API design/integration background (REST/GraphQL, webhooks, OAuth/OIDC)
- Data integration experience: building pipelines, transforming/normalizing data, and connecting heterogeneous systems
- Experience building customized AI agents tailored to business workflows and integrating them into existing apps
- Solid software engineering practices: testing, CI/CD, versioning, code reviews, secure coding, documentation
- Python development experience (for AI tooling, data pipelines, or SDKs)
- Understanding of AI models and tradeoffs (context length, token costs, latency, safety, evals)
- Experience with AI frameworks and components: Semantic Kernel, LangChain, function calling, vector search (e.g., Azure AI Search, Pinecone, Redis, pgvector)
- RAG patterns (indexing, chunking, embeddings, metadata), prompt engineering, evaluation frameworks
- Cloud experience (Azure preferred; AWS/GCP welcome), containers (Docker), and basic DevOps
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