Full-Stack (Platform) - Mid/Senior Level - Ref. 86ca1xaf6

About Medicilio

At Medicilio, we build software that improves healthcare operations and patient experiences at scale.

We are a remote-first company with teams across multiple continents, building products for Italy today and expanding across Europe tomorrow.

You'll work closely with product, operations, clinical stakeholders, and external technical partners to solve complex real-world problems in a high-trust environment where ownership matters more than process.

We care about:

• shipping meaningful products that work in production,
• building systems that remain maintainable over time,
• learning fast and adapting continuously,
• and enjoying the process of building together.

Remote-first within the EU. Optional offices in Milan and Sicily.

About the role

This is a fullstack engineering role in an AI-assisted engineering environment. Modern engineering teams increasingly use AI systems to accelerate implementation and reduce repetitive work. This shifts engineering toward system design, architectural judgment, quality ownership, and shaping how software is delivered.

At Medicilio, engineers own outcomes, not just implementations. You are responsible for what ships — ensuring it is correct, secure, and sustainable in production.

We operate an artifact-driven delivery model:

• work is broken into structured, reviewable units
• AI assists execution where appropriate
• engineers design, review, refine, and approve each stage before it progresses

Engineers are responsible not only for building systems, but for defining the boundaries within which AI and humans operate safely.

We expect teams to remain capable of shipping without AI when required. AI increases leverage — it does not replace engineering judgment.

What you'll do Own outcomes end-to-end

• Own features from definition through implementation, release, and iteration.
• Work with Product and Engineering to define scope, sequencing, and technical approach.
• Translate ambiguous product goals into clear technical plans and execution paths.

Design and evolve systems

• Design scalable, maintainable systems with clear boundaries and interfaces.
• Make architectural decisions that remain robust under production load and evolving requirements.
• Structure systems so both humans and AI agents can operate safely within them.
• Continuously improve systems through refactoring, simplification, and better abstractions.

Example: Restructured a backend service into explicit domain, integration, and infrastructure layers after repeated AI-generated PRs began creating architectural drift. Introduced clear boundaries and test contracts so future changes — human or AI-generated — cannot bypass system structure. This reduced review overhead and improved long-term maintainability.

Work with AI as part of production engineering

AI is part of the delivery system. Engineers are responsible for how it behaves within it.

This includes:

• deciding where AI is appropriate and where it is not
• shaping how work is decomposed for human vs AI execution
• defining constraints, guardrails, and review mechanisms
• continuously improving AI-assisted workflows over time

Example: After observing AI-generated PRs that were correct in isolation but misaligned with system architecture, introduced structured execution rules (CLAUDE.md + review checkpoints) that constrained agent behavior by design. This shifted output from "individually correct" to "systemically safe and consistent".

Shift review from code correctness to system correctness

You will review both human and AI-generated work.

We expect focus on:

• domain invariants
• system behavior under edge cases
• architectural consistency
• security and data integrity

Example: AI-assisted PRs consistently passed tests but introduced subtle domain inconsistencies in edge cases. Instead of fixing individual issues, introduced invariant-based review checklists and structured test patterns. This shifted review from implementation details to system behavior correctness and improved production reliability across services.

Quality, security, and production ownership

• Own what ships, including edge cases and production behavior.
• Participate in debugging, monitoring, and incident response.
• Maintain strong security and API design standards.
• Eliminate entire classes of failure modes, not just individual bugs.

Example: Detected a subtle cross-tenant data exposure issue in an AI-generated PR that passed automated checks. Instead of patching the bug, introduced stricter data access layering, reusable isolation tests, and updated agent constraints. This eliminated an entire class of data leakage risks across services.

How we work

We operate in small, high-trust squads with strong ownership and minimal process overhead.

A typical week includes:

• shaping and scoping upcoming work with Product and Engineering
• building and reviewing changes (often AI-assisted)
• debugging production issues when needed
• improving system architecture and developer workflows
• collaborating with clinical, operational, and technical stakeholders

We optimize for:

• clarity over process theater
• ownership over handoffs
• fast iteration with high standards
• continuous improvement of how we build software

Tech stack

• Python (Django / FastAPI)
• TypeScript (React)
• PostgreSQL
• Google Cloud Platform
• AI-assisted engineering workflows (Claude, Cursor, MCP, sandboxed agents)

What we're looking for Must-haves

• 3+ years of fullstack engineering experience.
• Strong backend experience in Python (Django or FastAPI).
• Strong frontend experience in TypeScript (React or Vue).
• Experience shipping production systems in collaborative environments.
• Strong systems thinking and architectural judgment.
• Strong PR review skills and attention to system correctness.
• Ability to operate in ambiguous, evolving technical environments.
• Experience using AI coding tools in real production workflows, with clear judgment on when they help and when they don't.
• Strong product thinking — ability to connect technical decisions to user and business outcomes.
• Security awareness and secure API design fundamentals.
• Strong communication skills across technical and non-technical stakeholders.
• Demonstrated adaptability across tools, domains, or responsibilities.

Nice-to-haves

• Italian language skills.
• Experience in healthcare or regulated environments.
• Familiarity with HL7, FHIR, or DICOM.
• Experience with observability, CI/CD, or cloud infrastructure.
• Experience improving engineering workflows or developer productivity.
• GDPR and data protection familiarity.

Skills that matter most in the AI era

As AI handles more implementation work, the most valuable engineering skills become:

• judgment over output
• systems thinking over isolated implementation
• architectural decision-making
• product understanding
• quality and security evaluation
• clear communication under ambiguity

We are looking for engineers who can think deeply, take ownership, and consistently raise the standard of what gets shipped.

Compensation

€40,000–€75,000 depending on experience.

Top of band is available for engineers who demonstrate strong ownership and proven ability to operate effectively in AI-assisted engineering environments.

Equity might be part of the package, with allocation and vesting discussed openly at offer stage.

Location

Remote-first within the EU.

Optional offices in Milan and Sicily.

Our values

Trust

We communicate directly, keep our word, and operate with high autonomy. Trust increases speed by reducing unnecessary process.

Care

We care about the people we work with and the problems we solve. We give honest feedback, support each other, and create space to learn from mistakes.

Curiosity

We stay open, ask questions, and continuously learn from systems, users, and each other.

Expansion

We take on ambitious problems and grow through them. We value progress over perfection.

Joy

We build serious systems without losing enjoyment in the process. Strong morale improves both outcomes and quality of work.

Apply

Make sure to use the job reference 86ca1xaf6 when applying