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AI Full Stack Developer (RAG/React/GenAI)

Akaasa Technologies
Charlotte, NC, United States
about 1 month ago
Apply on www.careerjet.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$128,400.0 - $192,600.0
Working hours
Regular working hours
Job source
www.careerjet.com

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Continuous Integration Python (Programming Language) Search Technologies Software Engineering Data Logging ReactJS Flask (Web Framework) Large Language Models
+8 more
Fastapi Kubernetes Low Latency Front End Software Development Restful APIs GPT Docker Microservices

Requirements

  • Hands-on GenAI/LLM application development experience.
  • Strong Python development experience.
  • Experience with FastAPI, Flask, REST APIs, microservices, or model inference endpoints.
  • Experience building RAG pipelines, including document ingestion, chunking, embeddings, vector search, retrieval, and citations.
  • Experience with LLM frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar.
  • MUST HAVE: React or modern front-end development experience.
  • Cloud deployment experience with AWS or Azure.
  • CI/CD, Docker, Kubernetes, monitoring, logging, or observability experience.
  • Ability to troubleshoot production AI applications, including retrieval issues, prompt issues, model behavior, latency, cost, and data quality.
  • Strong communication skills with the ability to translate business and engineering needs into technical solutions.

Benefits & conditions

  • $128,400-192,600 per year

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

40 sec

Generative pre-trained transformer models powering code completions

lgonta lgonta +1 · World Congress 2024

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

1:21 min

Exploring the target application for front end tests

Anna Mcdougall · JS Congress

3:14 min

Building a community-governed LAMP stack for open AI

Raffi Krikorian Raffi Krikorian · World Congress 2026 Europe

51 sec

Assessing GPT-4o performance for pull request feedback

Merrill Lutsky Merrill Lutsky · World Congress 2025

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

Videos

See all
Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS thumbnail
53:45
JS Congress • almost 5 years ago

Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS

Anna Mcdougall

Docker Compose: Rediscovered thumbnail
28:40
Europe 2026 Virtual • 2 months ago

Docker Compose: Rediscovered

Matthieu Vincent

Evaluating AI models for code comprehension thumbnail
22:03
World Congress 2025 • about 1 year ago

Evaluating AI models for code comprehension

Merrill Lutsky

Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps thumbnail
28:57
World Congress 2024 • about 2 years ago

Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps

David Leconte, Michel de Ru

Docker build without Docker thumbnail
28:40
World Congress 2026 Europe • about 2 months ago

Docker build without Docker

Oliver Seitz

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge thumbnail
42:26
Coffee With Developers • over 1 year ago

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge

Meta Atamel, Guillaume Laforge

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