AI Engineer

Zohorecruit

Polska

Hybrid

PLN 180,000 - 260,000

Full time

14 days+

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Job summary

Zohorecruit is seeking a skilled AI Engineer to design, build, and maintain local AI agents, private datasets, and automation solutions for internal and customer-facing projects. You will work with LLMs, private deployments, and vector databases to deliver secure, production-ready tools.

The role emphasizes private data handling, integration with internal systems, and building AI workflows that scale across business functions.

Qualifications

Bachelor’s degree in a relevant field (CS, software engineering, data science, AI).
2+ years in AI, ML, data engineering, or software development.
Experience with LLMs and AI application development.
API, database, and automation workflow experience.
Experience building RAG systems or document-based AI search.
Understanding embeddings, vector databases, and prompt engineering.
Ability to process unstructured documents (PDFs, Word, Excel, emails).
Strong documentation and communication skills.

Responsibilities

Design and build AI agents for internal and customer use cases.
Develop AI workflows that connect with internal systems (email, documents, helpdesk, PM tools, knowledge bases, databases).
Create tools for document search, summarization, classification, and report generation.
Implement private/local AI deployment with tools like Mistral, Qwen, Gemma, or DeepSeek.
Work with local AI tools and frameworks (LM Studio, vLLM, LangChain, AutoGen/CrewAI).
Ensure AI systems are secure, scalable, and privacy-compliant.
Create private datasets from company documents and maintain searchable knowledge bases.

Skills

AI development

LLMs

Python

APIs

Documentation

Data engineering

Vector databases

Security

Embeddings

Education

Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI, or related field

Tools

LangChain

vLLM

ChromaDB

Qdrant

FAISS

pgvector

PostgreSQL

Docker

React

Job description

We are looking for a skilled and practical AI Engineer to design, build, and maintain local AI agents, private datasets, and intelligent automation solutions for our internal operations and customer-facing projects.

The ideal candidate should be able to work with Large Language Models, local AI deployment, retrieval-augmented generation, vector databases, document processing, and workflow automation. This role is especially important for building secure AI systems that can run locally or privately, using company data without exposing sensitive information to public AI platforms.

The engineer will work closely with management, sales, technical teams, and operations to convert business knowledge, documents, processes, and customer data into usable AI agents and internal productivity tools.

Requirements

Key Responsibilities

AI Agents & Automation

Design and build AI agents for internal and customer use cases, such as:

Technical presales assistant
Proposal and BoQ generation assistant
ISO 9001 / compliance assistant
Customer support knowledge agent
Project documentation assistant
Network and cybersecurity advisory assistant
CRM and operations automation agents

Build AI workflows that can connect with internal systems such as:

Email
Document repositories
Helpdesk systems
Project management tools
Knowledge bases
Internal databases

Develop agents that can perform tasks such as document search, summarization, classification, recommendation, data extraction, report generation, and workflow triggering.

Local AI & Private Deployment

Implement AI models and applications that can run in private or local environments, including:

Private cloud
Local workstations

Evaluate, deploy, and optimize open-source LLMs such as:

Mistral
Qwen
Gemma
DeepSeek
Other suitable open-source models

Work with local AI tools and frameworks such as:

LM Studio
vLLM
LangChain
AutoGen / CrewAI or similar agent frameworks

Ensure AI systems are secure, scalable, reliable, and aligned with company data privacy requirements.

Datasets & Knowledge Bases

Create, clean, structure, and maintain private datasets from company documents, including:

Technical proposals
BoQs
SOPs
ISO documents
CRM records
Network and cybersecurity solution documents

Build and maintain searchable knowledge bases using:

Embeddings
Retrieval-augmented generation
Document chunking
Data classification
Access controls

Work with vector databases such as:

ChromaDB
Qdrant
Pinecone
Weaviate
FAISS
PostgreSQL with pgvector

Application Development

Develop user-friendly AI tools, dashboards, and internal applications using technologies such as:

Python
FastAPI
React / Next.js
Node.js
REST APIs
Docker

Build integrations with third-party systems through APIs, webhooks, and automation platforms.

Create proof-of-concepts and convert successful prototypes into production-ready tools.

Data Security & Governance

Ensure company and customer data is handled securely.

Implement controls for:

Data privacy
User access
Audit trails
Prompt logging
Hallucination reduction
Secure API usage
Backup and version control

Help define internal standards for using AI safely across the company.

Required Qualifications

The candidate should have:

Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI, or related field.
2+ years of experience in AI, machine learning, data engineering, or software development.
Practical experience with LLMs and AI application development.
Experience with APIs, databases, and automation workflows.
Experience building RAG systems or document-based AI search.
Good understanding of embeddings, vector databases, and prompt engineering.
Ability to work with unstructured documents such as PDFs, Word files, Excel sheets, emails, and knowledge base articles.
Ability to turn business requirements into working AI solutions.
Good documentation and communication skills.

Preferred Qualifications

Strong candidates will also have experience with: