Software Engineer (Data & AI) – Healthcare

Quick Facts

Mid-level Software Engineer building end-to-end data and AI systems for healthcare.

• Role: mid-level engineer working across classical ML and LLM-based agents, including data pipelines, cloud, and production integrations
• Work model: fully remote; team mainly in Poland (Poznań area) with quarterly in-person retreats
• Language: fluent English and fluent Polish (Polish is a hard requirement)
• Contract: B2B or mandate; flexible hours

Description

Design, build, deploy, and improve production-grade healthcare data and AI systems, from NLP/LLM documentation automation and imaging models to MLOps and data platforms. You’ll own components and, over time, lead project streams and architecture decisions. The work is compliance- and integration-heavy, with real user and patient impact.

Responsibilities

• Design AI/data solutions with careful product and compliance constraints
• Implement extraction and automation steps and supporting components
• Deploy changes, debug issues via logs, and add regression tests
• Ship features to development for fast client visibility when needed
• Contribute reusable components to a shared library
• Support cross-team knowledge sharing and iterative improvements

Requirements

• 3+ years of software and ML/AI engineering
• Problem-solving mindset beyond task execution; ability to engage with client business needs
• AI power-user mindset: hands-on use of LLMs/agents and regular industry follow-through
• Genuine interest in healthcare; authentic motivation to build tech affecting patient care
• Full-stack engineering mindset: Python/AI core with comfort working across infra and pipelines
• Fluent English and fluent Polish (written and spoken); Polish is mandatory

Benefits

• Real impact: production systems used by medical clients affecting patients and public health
• Frontier approach: adopt new models and tools quickly when they make sense
• End-to-end ownership: across ML, data, infrastructure, and user-facing applications
• Direct influence: impact projects and direction
• Flexible remote work: fully remote with flexible hours
• Learning & growth: training budget, weekly learning sessions, funded certifications, research opportunities, and hackathons

Hiring Process

• Engineering team CV pre-selection
• Intro call (5–10 minutes)
• Short take-home coding task (up to ~1 hour; flexible scheduling window)
• Technical interview with two engineers
• Conversation with the CEO
• Remaining steps typically completed within ~2 weeks after pre-selection