We are looking for a
Backend Developer
with hands-on production experience building real-world AI systems—including RAG pipelines, AI agents, and LLM integrations—running on AWS.
This role is for someone who lives in the code, not just in theory.
✅ What this means:
- Active Coder:
Strong daily production experience writing services in
Python and/or Java
. 3yoe
- Production-Grade AI:
Proven track record of building and deploying RAG pipelines, AI agents, or LLM-powered tools to live environments.
- Cloud AI Stack:
Hands-on experience with cloud AI platforms (
AWS Bedrock preferred
; Azure OpenAI or GCP Vertex also accepted).
- Architecture & Depth:
Able to explain
*how*
they built it—specific tools used, architectural decisions made, and technical tradeoffs.
❌ What this does NOT mean:
- A QA/SDET looking to "transition into AI"
- A Data Engineer who builds ETL or data pipelines but lacks experience with application services.
- An ML Researcher who trains models from scratch but has never shipped a production backend service.
- An Architect or Product Manager who hasn't written code in 2+ years.
- Someone whose only "AI experience" is using ChatGPT or Cursor as a coding assistant.
Mandatory Skills Description
• AWS Bedrock — hands-on: model access, Knowledge Bases, Lambda integration (primary AI platform
•
AI agents & Agentic tooling
— practical knowledge of designing and operating AI agents, including agentic workflows, reusable skills, rules/guardrails, commands, and multi-tool/multi-agent orchestration
•
RAG pipeline
— end-to-end implementation: chunking, embedding, vector indexing, retrieval, generation
• Prompt engineering — zero-shot, few-shot, chain-of-thought, structured output (JSON mode), multi-turn
• Vector databases — working knowledge of OpenSearch, Pinecone, or Faiss; understands vector vs. graph DB difference
•
LLM guardrails
— input/output filtering, hallucination mitigation strategies
• Fine-tuning vs. RAG — ability to reason through which
📌 Senior Backend AI Engineer (México)
🏢 Luxoft
📍 México