Full Stack Developer - AI Integration

ASCENDING-posted 4 days ago

Full-time • Mid Level

Hybrid • Washington, DC

11-50 employees

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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.

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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