Lead AI Engineer — LLM Apps & Data Platform Systems

Vecten; Województwo mazowieckie; On-site; PLN 250,000 - 420,000; Full time

Job summary

Vecten in Warsaw seeks an experienced ML/Data Engineer to design and ship LLM-powered applications within a data platform. You will build prompt pipelines, RAG, and retrieval systems, and deliver MCP servers exposing data to AI agents.

You will integrate OpenAI and other providers, implement enterprise authentication, work with Snowflake and Pinecone, and contribute to data pipelines while documenting design decisions for production-ready solutions.

Qualifications

Responsibilities

• Design and ship LLM-powered applications from concept to production.
• Deliver MCP servers that expose data and services to AI agents and applications.
• Implement the security and authentication layer around them: enterprise authentication, IdP integrations, OAuth/OIDC flows.
• Consume external APIs and wrap them into services – web services, traditional APIs, or basic UIs.
• Integrate LLM providers into client systems.
• Build semantic search and retrieval on vector databases (Pinecone).
• Query, process, and analyze data in Snowflake using SQL and Python.
• Prepare datasets that feed AI features and analytics.
• Contribute to data pipelines when needed.
• Document design decisions before implementation.
• Claude Code is your primary delivery environment.

Skills

LLM-powered apps

Prompt pipelines

RAG

Retrieval

Security/authentication

OAuth/OIDC

APIs

LLM providers

Semantic search

Vector databases

Snowflake

SQL

Python

Data pipelines

Documentation

Claude Code

Agentic engineering

Tools

Snowflake

Pinecone

Claude Code

OpenAI API

Job description

Vecten in Warsaw seeks an experienced ML/Data Engineer to design and ship LLM-powered applications within a data platform. You will build prompt pipelines, RAG, and retrieval systems, and deliver MCP servers exposing data to AI agents.

You will integrate OpenAI and other providers, implement enterprise authentication, work with Snowflake and Pinecone, and contribute to data pipelines while documenting design decisions for production-ready solutions.