NoFluffJobs Hybrydowo Mid

AI Engineer

Mindbox Sp. z o.o.

⚲ Kraków

28 350 - 29 400 PLN (B2B)

Wymagania

  • Python
  • Java
  • Node.js
  • REST API
  • GraphQL
  • Microservices
  • React
  • TypeScript
  • AI
  • SQL
  • Elasticsearch
  • Docker
  • Kubernetes
  • Cloud platform
  • AWS
  • GCP
  • DevOps
  • IaC
  • Terraform
  • OWASP (nice to have)

Opis stanowiska

O projekcie:
At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe. 

You will design, build, and ship end-to-end AI-powered products, working on every layer from data/API integration and model enablement to secure, scalable front-end applications. The initial focus will be building a skill inventory to streamline AI project development based on best practices.

Sounds like your kind of challenge? 

#LI - Hybrid: 2x/week from the office in Kraków

What you get in return

- Flexible cooperation model – choose the form that suits you best
(B2B, employment contract, etc.)
- Hybrid work setup – 2x/week from the office in Kraków
- Collaborative team culture – work alongside experienced professionals eager to share knowledge 
- Continuous development – access to training platforms and growth opportunities 
- Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more 
- High quality equipment – laptop and essential software provided

Wymagania:
- Strong software engineering background with full-stack delivery experience.
- Backend: Python and/or Java/Node.js, REST/GraphQL APIs, microservices.
- Frontend: React/TypeScript (or an equivalent modern framework).
- Familiarity with AI/ML, including LLMs, embeddings, RAG pipelines.
- SQL and experience with document stores/search (e.g., Elasticsearch, vector DBs).
- Hands-on knowledge of Docker, Kubernetes, and one cloud platform (Azure, AWS, or GCP).
- Proficiency in DevOps: CI/CD, IaC (Terraform), monitoring/logging tools.
- Strong understanding of secure coding and OWASP principles.

Nice-to-have:

- Experience with agentic workflows and orchestration frameworks.
- Knowledge of model governance, explainability, and responsible AI controls.
- Background in building developer platforms or reusable AI components.
- Prior exposure to regulated environments (e.g., financial services).

Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.

Codzienne zadania:
- Develop and maintain full-stack AI applications (web UI, backend services, AI/ML components).
- Build LLM-enabled services: prompting, RAG, tool/function calling, evaluation, guardrails.
- Create and integrate APIs and microservices with enterprise systems and data sources.
- Implement data pipelines for ingestion, transformation, and retrieval (including vector stores).
- Craft front-end experiences for AI features like chat, copilots, workflow assistants, dashboards.
- Manage and enforce MLOps/LLMOps best practices (CI/CD, model/version management, monitoring).
- Define and execute testing strategies: unit, integration, offline evals, performance testing.
- Optimize for latency, cost, and reliability using modern engineering strategies.
- Ensure security, privacy, and compliance-by-design in every solution.
- Collaborate cross-functionally with UX, data, and product teams to deliver measurable results.

🔍 Dekoder Ogłoszenia

🔴
design, build, and ship end-to-end AI-powered products, working on every layer from data/API integration and model enablement to secure, scalable front-end applications
Oznacza to, że będziesz odpowiedzialny za cały cykl życia produktu AI, od początkowej koncepcji po wdrożenie i utrzymanie, co może być bardzo szerokim zakresem obowiązków.
🔴
The initial focus will be building a skill inventory to streamline AI project development based on best practices.
Pierwsze zadanie może być bardziej związane z organizacją i dokumentacją niż z bezpośrednim tworzeniem zaawansowanych modeli AI, co może być rozczarowujące dla kogoś szukającego czystego ML.
🟡
Flexible cooperation model – choose the form that suits you best (B2B, employment contract, etc.)
Chociaż elastyczność jest dobra, często oznacza to preferencję pracodawcy dla modelu B2B, który niesie ze sobą inne obowiązki i ryzyko dla pracownika.
🟡
Collaborative team culture – work alongside experienced professionals eager to share knowledge
Może oznaczać, że zespół jest mały i wszyscy muszą sobie pomagać, co jest pozytywne, ale może też sugerować, że brakuje dedykowanych ekspertów w poszczególnych dziedzinach.
🔴
Strong software engineering background with full-stack delivery experience.
Choć wymagane są umiejętności AI/ML, nacisk na 'strong software engineering background' i 'full-stack delivery' może sugerować, że rola bardziej skupia się na budowaniu aplikacji wokół AI, a nie na głębokim badaniu i tworzeniu samych modeli.