[No German required] - Part-Time Software Engineer - Full-Stack with AI (m/f/d)

Backend: Design and implement services/APIs (Python; Django a plus). Own performance, security basics, and error handling.

Data & SQL: Model schemas, write performant queries, handle migrations, and debug data issues.

DevOps/Cloud: Improve CI/CD; containerize services; contribute to infra as code (Terraform); work with GCP (incl. basic Kubernetes operations).

AI/ML (Plus): Prototype RAG pipelines, evaluate embedding/vector store choices, and integrate agentic workflows.

Frontend: Deliver product UIs with JS/TS (React a plus), apply state management patterns (Redux Toolkit), and use design frameworks (Material UI / Ant Design).

Quality & Collaboration: Add tests (unit/integration/e2e), perform code reviews, write clear docs, and communicate crisply.

Must-Have Qualifications

• Strong software engineering fundamentals and Git proficiency (branching, rebasing, PR hygiene).

• Solid experience with at least one backend language (Python preferred; Django a plus).

• Practical SQL skills (schema design, joins, indexing, query debugging).

• Working familiarity with CI/CD and cloud concepts; exposure to Terraform, GCP, or Kubernetes is valued.

• Comfortable contributing to frontend codebases; experience with modern JS frameworks (React a plus).

• Bachelor’s or Master’s degree (completed or in progress) in CS/SE or related field.

• Excellent English (written & spoken).

Nice to Have

• TypeScript in production; API design (REST/GraphQL).

• Observability (logs, metrics, traces) and security best practices (OWASP).

• AI/ML familiarity: vector databases, embeddings, RAG, lightweight agents/tool-use.

What “Great” Looks Like (Professional Traits)

• Ownership: clarifies goals, proposes options, and drives work to completion.

• Bias to impact: balances ideal solutions with delivery speed and maintainability.

• Communication: concise async updates, thoughtful PRs, transparent trade-offs.

• Quality discipline: tests where they matter, automates repeated tasks, documents decisions.

• Collaboration: respectful partner to product/design/ops; low-ego, high-initiative.

• Reliability: predictable availability and honest estimates.

• Learning mindset: curious about new tools but pragmatic in adopting them.

• Ethics & security: mindful of data privacy, licenses, and responsible AI usage.

Role Summary

We’re hiring a hands-on engineer who can contribute across the stack: build reliable backend services, ship practical UIs, own SQL/data work, automate CI/CD, and help us explore AI features (RAG, agentic patterns).

Practicals

• Hours: 20–30/week, flexible within EU business hours.

• Preferred Working Style: Face-to-face, hybrid (still negotiable)

• Compensation: Competitive; commensurate with experience and time commitment.

• Tooling: GitHub/GitLab, CI (e.g., GitHub Actions), Docker, Terraform, GCP, Kubernetes, Python/Django, JS/TS (React as needed).

Why Us

• Real impact, not ticket-churn. You’ll ship features end-to-end—scoping, building, testing, deploying—and see your work used by real customers quickly.

• Breadth by design. Backend, data/SQL, CI/CD, cloud, a touch of frontend, and space to explore AI (RAG, agentic patterns). We won’t pigeonhole you.

• Pragmatic engineering culture. We value clean code, clear interfaces, tests where they matter, and automation over toil—without gold-plating.

• Modern stack. Python/Django, SQL, JS/TS with React as needed, GitHub Actions CI, Docker, Terraform, GCP, Kubernetes, and observability from day one.

• Autonomy with support. You’ll own projects, make technical decisions, and get fast feedback from peers who care about code reviews and documentation.

• Flexible part-time fit. 20-30 hrs/week, EU time zones, async-friendly. We plan around focus time—not constant meetings.

• Learning & growth. Budget for courses/books, time for spikes/prototypes, and opportunities to lead initiatives as you grow.

• Product-first mindset. Engineers collaborate directly with design and product; you’ll influence roadmaps, not just implement them.

• Transparent processes. Clear goals, written decision records (ADRs), and straightforward hiring/performance feedback.

• Inclusive & respectful. Low-ego teammates, and a commitment to diversity and equal opportunity.

• Fair compensation. Competitive hourly/contract rates, with adjustments for expertise and added responsibility.

• If you want a part-time role where you can stretch across the stack, make measurable impact, and keep leveling up—this is it.

Learning Opportunities

• AI in production: Prototype and ship RAG pipelines end-to-end, compare embeddings/vector DBs, measure retrieval quality, and integrate agentic/tool-use workflows into real features.

• System design at small scale with big impact: Own services from API contract to deployment, practicing pragmatic design, performance tuning, and secure-by-default patterns.

• Cloud & platform skills: Get hands-on with Terraform, GCP, Kubernetes, Docker, and GitHub Actions—learning infra-as-code, basic K8s operations, and CI/CD automation.

• Observability & reliability: Instrument logs/metrics/traces, set SLOs, and use dashboards/alerts to drive root-cause analysis and continuous improvement.

• Data engineering fundamentals: Model relational schemas, optimize queries and indexes, manage migrations safely, and learn data quality/debugging techniques.

• Modern frontend craft: Build React/TypeScript UIs with Redux Toolkit and Material UI/Ant Design, focusing on state management, accessibility, and component design.

• Quality discipline: Write unit/integration/e2e tests with a risk-based mindset; practice test automation and CI gating to keep releases reliable.

• Security & privacy basics: Apply OWASP practices, handle secrets, and reason about data access, licensing, and responsible AI usage.

• Ownership & leadership reps: Drive small projects, write ADRs, lead design reviews/PRs, and mentor peers as you grow—without needing a formal title.

• Career support: Dedicated budget for courses/books, time for spikes/prototypes, and personalized guidance to deepen expertise or broaden across the stack.