Software Development Engineer

Summary

A junior Python engineer builds AI-powered document processing tools (PDFs) in a Dublin-based team, focusing on LLM-driven workflows, embeddings, and semantic search while learning from senior developers.

Junior Software Engineer (AI & Document Systems)

Location: Ireland (Hybrid — Dublin area)

Type: Full-time

About the role

Foxit is hiring a Junior Software Engineer to join our Ireland-based team building AI-powered, document-centric applications. This role is a strong fit for a recent graduate or early-career engineer with solid Python fundamentals and genuine curiosity about LLMs and document systems.

You’ll learn by doing—working alongside senior engineers to build and improve software that processes, manages, and analyses documents (especially PDFs) using modern AI techniques.

What you’ll do

Develop and maintain Python-based applications and services

Support delivery of AI-powered features using LLMs in document workflows

Assist with prompting and context management for document-focused use cases

Contribute to document ingestion and management workflows

Help process and extract information from PDF documents (text + structure basics)

Work with embeddings and introductory semantic search concepts

Write clean, tested, and well-documented code

Collaborate via code reviews, team discussions, and iterative delivery

Take direction from team leads and grow your skills through mentorship

What you’ll bring (required)

Bachelor’s degree in Computer Science / Software Engineering (or related)

Strong Python skills and good software fundamentals

Foundational understanding of AI and LLM concepts

Exposure to prompting and LLM-driven workflows (coursework, projects, internship, etc.)

Basic knowledge of document management concepts

Familiarity with PDF structure and text extraction concepts

Strong problem-solving mindset and willingness to learn quickly

Nice to have (bonus)

Introductory experience with RAG concepts

Familiarity with embeddings and/or vector databases

Exposure to vLLM, Ollama, or similar tooling

Basic understanding of REST APIs

Awareness of data privacy and GDPR principles

What success looks like

You ramp quickly on our codebase and ship reliable improvements

You collaborate well (communication, reviews, asking good questions)

You build confidence in LLM/document workflows while strengthening engineering fundamentals

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What this application asks

lever

Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Other website

What languages are you able to speak? written answer
What is your salary expectations? written answer
What is your notice period? written answer
What is the earliest you're able to start? written answer
Are you legally authorized to work in the location you are applying for without sponsorship? choose one · optional
Please briefly summarize your key experience relevant to this position: written answer
Tell me about the most impactful AI + document system you’ve built in production. What problem did it solve, what was the architecture (ingestion → retrieval/RAG → serving), and what did you personally own end-to-end? written answer
Walk me through a time your RAG/semantic search quality wasn’t good enough. How did you diagnose it (data, chunking, embeddings, prompts, evals), what changes did you make, and what measurable improvement did you see? written answer
Describe the hardest “PDF reality” problem you’ve dealt with. Messy layouts, tables, scans/OCR, metadata issues, multilingual docs—how did you handle extraction + structure, and what trade-offs did you make to keep it reliable at scale? written answer
Where are you currently based? choose one · optional

Summary

What this application asks

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See also