Full Stack AI Engineer

NTT DATA North America

3d•Remote

About The Position

As a Full Stack AI Engineer with NTT DATA, you’ll play a hands-on role in building modern, AI-enabled applications that help our clients transform their businesses. 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. This role is ideal for someone who thrives in dynamic client environments, enjoys solving complex engineering challenges, and stays ahead of the curve in modern AI and cloud technologies.

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.
Cloud certifications (Azure/AWS/GCP) and Agile/Scrum delivery experience.
Consulting background or experience delivering to regulated enterprises.

Responsibilities

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.