Codesmart

CodeSmart is seeking an experienced and proactive Senior Python Developer to join our growing engineering team. The ideal candidate has a deep understanding of Python, extensive experience building scalable web applications with Django, and a strong background in distributed systems using Celery and RabbitMQ. You will also be responsible for designing and integrating features powered by OpenAI and other LLM APIs, helping us build intelligent, AI-driven products.

As a Senior Python Developer, you will own core parts of the backend architecture, mentor other engineers, and work closely with product and cross-functional teams to deliver robust, high-quality solutions.
 

Responsibilities:

• Design, develop, and maintain backend services using Django framework and Fast API.
• Architect and optimize asynchronous task processing using Celery and RabbitMQ.
• Design and implement features that leverage OpenAI and other LLM APIs (e.g., content generation, assistants, search, classification, and summarization).
• Take ownership of technical solutions from design through deployment, monitoring, and iteration.
• Collaborate with product managers, designers, and other developers to define and implement new features.
• Write efficient, reusable, testable, and well-documented code.
• Participate in and lead code reviews, ensuring code quality, performance, and adherence to best practices.
• Design and optimize Postgres database schemas, queries, and migrations.
• Use Docker to containerize applications and support deployment workflows.
• Diagnose, troubleshoot, and resolve complex production issues.
• Mentor Middle and Junior developers, providing technical guidance and knowledge sharing.
• Stay current with industry trends, especially in LLMs, AI/ML tooling, and backend technologies, and bring relevant ideas into the team.
   

Requirements:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience).
• 6+ years of commercial experience in Python backend development.
• Strong hands-on experience with the Django framework.
• Proven production experience integrating and working with OpenAI and other LLM APIs (e.g., prompt design, handling context windows, managing costs and rate limits).
• Experience building AI-powered features or workflows on top of LLMs (chatbots, assistants, content generation, semantic search, etc.).
• Strong knowledge of Object-Oriented Programming, design patterns, and application architecture.
• Proficiency with Postgres SQL: schema design, indexing, query optimization.
• Practical experience with Docker for development and deployment.
• Strong debugging, performance optimization, and problem-solving skills.
• Experience with Git.
• Experience working in Agile environments Scrum/Kanban.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and CI/CD.
• Excellent communication skills and the ability to collaborate effectively in a distributed team.
• Experience building AI-powered features: content generation, interactive workflows, structured output parsing, prompt design
• Solid production experience with Celery + RabbitMQ (retries, task states, error handling, restart resilience)
• Strong knowledge of Docker & Docker Compose for development and deployment of multi-container applications

If you have real-world prompt examples from production projects (chatbots, interactive story generators, agents, RAG pipelines with multi-step reasoning), please highlight them in your cover letter or include GitHub links. This will significantly speed up the review process.
 

If you’re passionate about building scalable backend systems and excited to work at the intersection of Python and LLM-powered applications, we’d love to hear from you.

What you will be doing:

Building a comprehensive test automation system (from unit to end-to-end)

Quickly identifying key steps for maximum automation

Ensuring process quality, not just testing

Optimizing regression coverage in an environment with a large number of products and releases

Your role:

Lead the team (manual testers + automation engineers)

Assign tasks and develop specialists

Manage work processes and improve quality

Must have:

Experience in building and scaling QA processes

Understanding of how to create maximum value with minimum effort

Leadership skills in managing a team of QA engineers

Join us to take quality to the next level!

Amplifier AI is building a next-generation surgical planning platform - powered by our own imaging, segmentation, and 3D measurement engine.

We are a focused team of engineers, radiologists, and data scientists from Ukraine and across Europe. We care about precision, reproducibility, and building tools that genuinely help doctors plan safer surgeries.

If you enjoy clean Python, 3D geometry, and solving real-world imaging problems - keep reading.

Why Amplifier

Real impact

Your work directly influences clinical decisions and patient outcomes.

Deep technical domain

Medical imaging is one of the most intellectually demanding areas in applied software engineering. You’ll work at the intersection of geometry, physics, and clinical reality.

Growth

Competitive salary, optional stock options, and a clear path toward senior-level ownership.

Engineering culture

Small team. Thoughtful discussions. Strict typing. Strong code reviews. No corporate theater.

How We Work

• Fully remote, with EU time overlap
• Communication in English / Ukrainian
• Ownership over micromanagement
• Code reviews are deep and technical (we care about correctness, not ego)

We move fast - but with engineering discipline.

Hospitals and real clinical data sometimes change priorities.

When that happens, we adjust together as a team.

This is not an enterprise environment with fixed roadmaps and perfectly predefined tickets.

It’s a product used in real surgeries - responsibility matters.

This Role Is Probably Not For You If

• You prefer fully predefined tasks with minimal ambiguity.
• You optimize mainly for comfort and predictability.
• You’re looking for a low-pressure role to focus on side projects.
• You want to “just implement tickets” rather than understand the domain.

We’re building production software used in hospitals.

Quality and ownership are part of the job.

What You’ll Work On

You’ll join the team developing our internal Python engine that powers 3D reconstruction and measurement logic for CT-based workflows.

Your responsibilities will include:

SimpleITK & DICOM

• Reading DICOM series correctly
• Validating RAS origins and directions
• Resampling safely
• Maintaining voxel ↔ physical transforms

VTK & Geometry

• Surface generation from labels
• Distance, intersection, and clipping algorithms
• Exporting reliable STL markers and geometry artifacts

Measurement & QA Logic

• Building robust procedural tools for radiologists
• Handling edge cases in real hospital data

Pipeline Reliability

• Performance tuning
• Structured logging
• Making sure pipelines survive messy real-world datasets

You will own features end-to-end:

from understanding the problem to validating on real data.
 

Our Stack

Core:

• Python 3.13+
• SimpleITK
• VTK
• NumPy / SciPy
• Pydantic

ML:

• PyTorch
• nnU-Net (segmentation experiments)

Tooling:

• pytest
• mypy (strict)
• ruff
• pre-commit
• Docker
• GitHub Actions
• Git LFS
• Sentry

We write clean, typed code.

Reproducibility is mandatory.

We prefer clarity over cleverness.

What We’re Looking For

We’re not hiring by title.

We’re hiring engineers who think clearly and care about correctness.

You’ll thrive here if you:

• Write clean, modular Python code
• Understand 3D medical image fundamentals (origin, spacing, direction)
• Know the difference between voxel space and physical space
• Enjoy debugging complex geometric edge cases
• Can explain your reasoning clearly

Experience with SimpleITK, VTK, or PyTorch is a strong plus.

If you haven’t used them before, you must be comfortable diving deep and learning independently.

We mentor - but initiative is expected.
 

Nice to Have

• VTK surface/volume rendering experience
• ML segmentation metrics (Dice, Hausdorff, nnU-Net)
• Interest in GPU acceleration and large-volume performance

Example Challenges

• Build a robust distance-measurement tool between anatomical segmentations with exportable nearest-point markers.
• Extract centerlines and anatomical landmarks from noisy CT scans.
• Enforce consistent spacing/origin/direction across multi-scanner datasets.

If these sound exciting rather than overwhelming - you’ll likely enjoy this role.

What You’ll Gain

• Deep expertise in medical imaging geometry
• Exposure to production-grade clinical data
• Mentorship in system design and performance optimization
• Opportunity to grow technical lead responsibilities over time

We invest in engineers who invest in the product.

How to Apply

Send us:

• Your CV or LinkedIn
• Your GitHub or portfolio (we value real code)
• A short note answering:

A Note from Us

We are Ukrainian engineers building software that blends science and purpose.

We don’t build hype.

We build tools that work in real clinical environments.

If you’re curious, precise, and ready to take ownership - we’d love to talk.