Senior Applied AI Engineer
New
F
FlypsAI software
100% remote setupContractSenior
Salary26,000 - 33,000 PLN per month
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Job Details
- Languages
- Polish C2 and English C1
- Required Skills
- DockerPythonArtificial IntelligenceGitFastAPILLM
Requirements
- Strong software engineering skills and experience building production applications.
- Hands-on experience with LLM-powered systems, including LLM APIs, tool calling, structured outputs, and multi-step workflows.
- Experience with RAG, vector search, or agent-based architectures.
- Experience building backend services and APIs, preferably with FastAPI.
- Experience with automated testing, Git, and code review.
- Practical experience with LLM evaluation and observability, including measuring quality, failures, latency, and cost.
- Strong technical problem-solving skills and ability to make sound architectural trade-offs.
- Experience providing technical guidance through architecture decisions, code reviews, and mentoring.
- Ability to explain technical decisions, challenge assumptions, and work effectively with clients and engineers.
- Comfort using AI-powered coding assistants such as Cursor, GitHub Copilot, ChatGPT, or Claude.
- Comfort working in a bilingual environment: Polish C2 and English C1.
Responsibilities
- Design and develop LLM-powered systems from prototypes to production.
- Diagnose and improve AI systems by analysing code, data, logs, and execution traces.
- Choose the right approach, from simple workflows to agentic architectures.
- Build evaluations and regression tests to measure quality and detect failures.
- Run experiments comparing solutions across quality, cost, latency, and reliability.
- Build backend services and API integrations, including validation, error handling, logging, and monitoring.
- Work with clients to define requirements and acceptance criteria, and communicate technical decisions, results, and limitations.
- Set technical direction, review solutions, and support engineers through mentoring and collaborative problem-solving.
- Evaluate new models, tools, and approaches and validate their practical value before recommending them for production.
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