Full-Stack AI Engineer: Build Agentic Apps & Workflows

Accenture; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Accenture Data & AI is seeking a hands-on Full Stack AI Consultant (Developer) to design and deliver production-grade agentic AI solutions. You will build full stack AI applications, integrate agents and tools, and maintain DevOps/AgentOps practices.

Daily coding, knowledge pipelines, and system observability are core expectations. The role emphasizes building MCP servers, memory architectures, and RAG pipelines while staying current with evolving agentic AI technologies.

Qualifications

• 3+ years of full stack software engineering in production with Python backend and a frontend framework.
• 3+ years building and deploying LLM-based applications — prompt engineering, RAG, tool integration, or agent development.
• Hands-on experience with agentic AI frameworks — agents, tools, orchestration.
• 3+ years experience in classical AI/ML, data engineering, or analytics.

Responsibilities

• Design and build full stack agentic AI applications — Python backends, REST and event-driven APIs, and React frontends — to production engineering standards.
• Implement agentic application UX: streaming responses, intermediate output display, reasoning transparency, and error and escalation interfaces for end users.
• Build and configure agents using established orchestration frameworks (LangGraph, AutoGen, or equivalent).
• Implement context engineering pipelines, memory architectures, and LLM gateway configuration to support reliable operation.

Skills

Full stack Python

Frontend React

LLM apps

Cloud native

AI/ML basics

CI/CD

Version control

Education

Bachelor’s degree in CS or related field

Tools

LangGraph

AutoGen

CrewAI

MCP servers

Elasticsearch

Job description

Accenture Data & AI is seeking a hands-on Full Stack AI Consultant (Developer) to design and deliver production-grade agentic AI solutions. You will build full stack AI applications, integrate agents and tools, and maintain DevOps/AgentOps practices.

Daily coding, knowledge pipelines, and system observability are core expectations. The role emphasizes building MCP servers, memory architectures, and RAG pipelines while staying current with evolving agentic AI technologies.