AI Engineer—Build Production-Ready RAG & Agentic Workflows

Haptiq; Województwo mazowieckie; On-site; PLN 239,000 - 282,000; Full time

Job summary

Haptiq is seeking an innovative AI Engineer to join the AI team and help design, prototype, and operationalize advanced AI systems, including RAG pipelines and agentic workflows. You will collaborate with Python developers and MLOps engineers to bring AI-powered features to production.

Responsibilities include building AI-powered services, training ML models, and optimizing prompts while integrating vector databases like Chroma, FAISS, Pinecone, and Qdrant.

Qualifications

• Strong Python development skills with clean, scalable code.
• Hands-on experience with LLMs and agent frameworks.
• Familiarity with RAG architectures and vector search concepts.
• Experience building multi-step agentic workflows.
• Knowledge of AI performance metrics and model monitoring.
• Awareness of latency and explainability challenges.

Responsibilities

• Design, prototype, and iterate AI models and RAG pipelines.
• Develop AI-powered services using LangChain, LangGraph, CrewAI, LlamaIndex, and Haystack.
• Train and evaluate ML models for production use cases.
• Perform data preprocessing and feature engineering to boost performance.
• Tune architectures and hyperparameters for target performance.
• Implement validation pipelines and model monitoring in production.

Skills

Python

LLMs

Agent frameworks

RAG pipelines

Model evaluation

Experimentation

System design

Performance metrics

Education

BSc in CS or equivalent

Tools

LangChain

LangGraph

CrewAI

LlamaIndex

Haystack

Job description

Haptiq is seeking an innovative AI Engineer to join the AI team and help design, prototype, and operationalize advanced AI systems, including RAG pipelines and agentic workflows. You will collaborate with Python developers and MLOps engineers to bring AI-powered features to production.

Responsibilities include building AI-powered services, training ML models, and optimizing prompts while integrating vector databases like Chroma, FAISS, Pinecone, and Qdrant.