AI Engineer

BraverIT; Kraków; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

BraverIT in Krakow is seeking an experienced backend/AI engineer to build production-grade LLM systems, applying RAG, embeddings, and semantic search to real products.

You will design APIs with Python (FastAPI), implement CI/CD for models, deploy on AWS, and manage Docker/Kubernetes workflows, collaborating with Data Science and Product teams in an international setting.

Qualifications

• Experience building production APIs.
• Hands-on with deploying LLM-based systems.
• Knowledge of RAG, embeddings and semantic search.
• Experience with AWS and scalable backend design.
• Strong Docker, Kubernetes and CI/CD understanding.
• Proven PoC-to-production experience.

Responsibilities

• Build and maintain production-grade LLM systems (including RAG, semantic search, embeddings, vector databases).
• Design and develop APIs and microservices in Python (e.g. FastAPI).
• Develop and maintain CI/CD pipelines for models (LLMOps/MLOps).
• Deploy and manage infrastructure in AWS (Lambda, ECS/EKS, S3, API Gateway, CloudWatch).
• Implement containerisation (Docker) and orchestration (Kubernetes).
• Monitor model quality (latency, drift, hallucinations, cost efficiency).
• Collaborate closely with Data Science, ML, Data Engineering and Product teams.

Skills

Python

LLM deployment

AWS

Docker

Kubernetes

CI/CD

Tools

FastAPI

S3

ECS/EKS

CloudWatch

Job description

You will join a team building next-generation AI-powered products based on Large Language Models. The project focuses on transforming LLM prototypes into scalable, secure, and production-grade systems. The role covers the full AI lifecycle – from architecture and backend development to infrastructure, monitoring, and cost optimisation.

Your responsibilities

• Build and maintain production-grade LLM systems (including RAG, semantic search, embeddings, vector databases).
• Design and develop APIs and microservices in Python (e.g. FastAPI).
• Develop and maintain CI/CD pipelines for models (LLMOps/MLOps).
• Deploy and manage infrastructure in AWS (Lambda, ECS/EKS, S3, API Gateway, CloudWatch).
• Implement containerisation (Docker) and orchestration (Kubernetes).
• Monitor model quality (latency, drift, hallucinations, cost efficiency).
• Collaborate closely with Data Science, ML, Data Engineering and Product teams.

Our requirements

• Strong Python skills with experience building production APIs.
• Hands-on experience deploying LLM-based systems in production.
• Practical knowledge of RAG, embeddings, vector databases, and semantic search.
• Experience with AWS and scalable backend system design.
• Solid understanding of Docker, Kubernetes and CI/CD.
• Proven ability to move from PoC to stable production solutions.

What we offer

• Opportunity to work on advanced AI systems with real product impact.
• Strong influence on architecture and technology decisions.
• Collaboration with an experienced Data & AI team in an international environment.
• Flexible andremote-friendly working mode