Senior GenAI Engineer (Python)

Quick Facts

Senior GenAI Engineer (Python) building cloud-native backend services for LLM-driven intelligent automation.

Description

Design, build, and optimize scalable backend systems in the cloud that power AI-driven and intelligent automation solutions. You will develop end-to-end LLM features (agentic flows, retrieval, tool calling) and ship them as FastAPI services with streaming, persistence, and proper tests. You will also own answer quality and debug production using tracing and performance/cost instrumentation.

Responsibilities

• Build LLM-powered features end to end: design and implement agentic flows, retrieval, and tool calling using LangGraph, then ship as FastAPI services with streaming, persistence, and proper tests.
• Own answer quality: create evaluation datasets, regression suites, and LLM-as-judge checks to verify whether prompt/model changes improve results before users see them.
• Get the right context to the model: turn user questions into effective queries for the search platform, orchestrate multi-step research loops, shape the context the model reasons over, and diagnose whether retrieval, query, or prompting caused incorrect answers.
• Debug production: instrument flows with Langfuse tracing, analyze bad answers from real traces, and manage latency, token, and cost budgets—including routing across model sizes/families behind an AI gateway.

Requirements

• Strong Python proficiency for backend development (FastAPI, Flask, Django, or similar).
• Deep understanding of software architecture, design patterns, and API development.
• Solid experience with Azure cloud services, including containerization (Docker, Kubernetes), storage, and serverless technologies.
• Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform, Bicep, ARM), and monitoring (App Insights, Prometheus, Grafana).
• General interest and experience with AI-driven applications and automation.
• Hands-on experience or strong understanding of AI-driven systems and intelligent automation workflows.
• Experience/knowledge of using LLM APIs and how such systems are tested; understanding of RAG and LangGraph.
• Ability to apply prompt engineering and integrate ML or LLM APIs effectively.
• Proven track record in building scalable, performant systems.
• Experience in code reviews, mentoring, and setting engineering standards.
• Strong problem-solving skills, analytical thinking, and technical decision-making.
• Fluent English; proactive communicator and collaborative team player.

Benefits

• Comprehensive benefits: Udemy for Business, private medical care, Multisport card, veterinary package, language lessons, and shopping vouchers.
• Flexibility: adaptable working hours and remote or hybrid work options.
• Career growth: professional development opportunities and benefits from partnerships with Microsoft, AWS, Snowflake, Salesforce, and other global technology companies.
• Global collaboration with a diverse, international team.
• Innovative environment to help shape modern AI and intelligent automation solutions.
• Engaging community: team-building events, hackathons, and CSR initiatives; annual company event in Mazury.
• Welcome pack to start your journey.