Wrocław, Wrocław, Lower Silesian Voivodeship, Polska
Rekrutacja 360 - Pracuj.pl
29. 11. 2025
Informacje o stanowisku
technologies-expected :
OpenAI
CI/CD
Kubernetes
AWS
Python
Go
Node.js
Embeddings
RAG
Anthropic
AWS Bedrock
GitHub Copilot
API
technologies-optional :
DevEx
about-project :
We are seeking a hands-on GenAI Tooling Engineer to integrate Generative AI (GenAI) technologies into our engineering workflows. This role is focused on building, prototyping, and deploying AI-powered solutions that boost developer productivity, improve engineering efficiency, and enhance the developer experience.
You will work directly with engineering teams to experiment, implement, and scale GenAI tools and integrations. The ideal candidate is a strong software engineer with experience applying LLMs and GenAI in real-world development environments.
responsibilities :
Work directly with developer and platform teams to design, build, and integrate GenAI solutions into engineering workflows (CI/CD, IDE extensions, test automation, documentation, code reviews, bug triage).
Prototype and deploy GenAI-powered tools, APIs, and plugins to accelerate developer productivity.
Implement retrieval-augmented generation (RAG) pipelines, embeddings, and vector databases to support contextual developer assistance.
Evaluate and productionize GenAI models and APIs (e.g., OpenAI, Anthropic, AWS Bedrock, GitHub Copilot).
Automate developer workflows using GenAI-assisted scripts, bots, and pipelines.
Collaborate with security, legal, and compliance teams to ensure safe, responsible, and compliant AI usage.
Collect and analyze developer productivity metrics to measure impact and iterate on solutions.
Stay current on GenAI trends and bring practical, emerging capabilities into the organization.
requirements-expected :
3–5+ years in software engineering, platform engineering, or developer productivity roles.
Hands-on experience implementing GenAI solutions in enterprise or production environments.
Proficiency in Python and ideally Go, Node.js, or similar.
Strong understanding of APIs, cloud services (AWS preferred), and containerized environments.
Experience working with LLMs, embeddings, vector databases, and RAG systems.
Familiarity with developer workflows, CI/CD, Kubernetes, and developer tooling ecosystems.