Full Stack AI Engineer

NTT DATA • Helena, GA

2d • Remote

About The Position

Working as part of a collaborative engineering squad, you'll develop fullstack features, design scalable backend services, and integrate cutting-edge agentic AI capabilities into real-world solutions. Design, implement, and maintain RESTful APIs Integrate userfacing experiences with serverside logic; ensure resilient API contracts for web and mobile clients (e.g., React Native). Implement robust testing (unit/integration/e2e), performance tuning, and production diagnostics. Build agentic AI workflows using tools like GitHub Copilot and LLM platforms (e.g., Claude, Azure OpenAI, OpenAI API, etc.). Implement tool/function calling, prompt/chain orchestration (e.g., LangChain/LlamaIndex), evaluation, safety guardrails, and prompt/version management. Deliver RAG patterns using embeddings and vector databases (e.g., Pinecone, FAISS, Redis, Azure AI Search/OpenSearch) to ground models on enterprise data. Design and deploy services on Azure (App Services, Functions, Storage, API Management; Azure DevOps/GitHub Actions pipelines). Use containers and orchestration (Docker, Kubernetes) and IaC (Terraform/Bicep). Implement observability (logs, metrics, tracing with OpenTelemetry), rate limiting, retries, circuit breakers, and cost/latency monitoring. Participate in discovery workshops, align on requirements, and convert client needs into technical plans and release roadmaps. Create clear documentation, demos, and walkthroughs; explain complex concepts to non-technical stakeholders.

Requirements

• 5+ years professional fullstack or backend experience, including React and Node.js/TypeScript
• 2+ years building LLM-integrated or agentic AI features (tool/function calling, orchestration, guardrails, or evaluations)
• 3+ years with Python for AI scripting, data processing, or service integration (FastAPI/Flask/Django a plus)
• Ability to travel up to 25% as needed

Nice To Haves

• Agent frameworks (LangChain, LlamaIndex); embeddings; vector databases (Pinecone, FAISS, Redis, Azure AI Search)
• Model lifecycle exposure: finetuning, adapters/LoRA, quantization, inference optimization, and safe deployment
• Kubernetes, API Management, GitOps, and advanced observability/telemetry
• Mobile collaboration (React Native) or designing API contracts for native clients
• Familiarity with FastAPI/Django (Python) or NestJS (Node); experience with Java in highscale backends
• Consulting background or experience delivering to regulated enterprises

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees