Summary
✨ AI‑Generated
Join a core AI engineering team responsible for taking advanced models and autonomous AI workflows from concept to production. You will build RAG and multi-agent applications, develop training and inference pipelines, optimize models for performance and cost, and deliver scalable enterprise AI systems.
Highlights
Experienced AI engineering role covering the full lifecycle of LLM and agent-based solutions, from design and training through production integration. The work emphasizes RAG, agentic and multi-agent systems, scalable data pipelines, and efficient cloud-native AI.
Description
Description:
We are seeking an experienced AI agents & LLM Engineer to join our core development team.
You will be responsible for the end-to-end lifecycle of our cutting-edge models - from design and training to integration into customer-facing products.
If you thrive on solving complex problems using AI agents & LLMs, possess expert-level Python skills and are driven by delivering tangible production value, this is your opportunity to shape our product innovation.
Key responsibilities:
Design, build and deploy solutions based on Machine Learning, LLMs and AI agents with a focus on enterprise production applicationsDevelop and implement AI-powered applications utilizing RAG, agentic workflows, multi-agent architectures and tool-calling frameworks.Build and optimize data pipelines for training, validation and inferenceOptimize models for performance, scalability and cost-effectivenessBuild scalable and cost-effective AI solutions leveraging cloud-native architectures.Conduct integration with applications (FastAPI, microservices)Implement MLOps and LLMOps processes, including automated training, testing, deployment, monitoring, evaluation, guardrails, and model retraining.Design agent orchestration frameworks and advanced reasoning workflows for autonomous and semi-autonomous AI systems.Integrate different AI models into production systems working closely with other engineering teamsCollaborate with data science, POs and IT teams to define requirements into implementationEnsure security, compliance, reliability, and observability of deployed AI solutions.
Key competencies:
Minimum 5 years of experience in Software Engineering, Machine Learning, Data Science or AI-related roles.Strong hands-on experience designing and deploying AI agents and LLM-based applications in production environments.Deep understanding of Transformer architectures, RAG systems, embeddings, vector databases, prompt engineering, context management and agent orchestration.Expert-level proficiency in Python and modern AI frameworks.Strong experience with LangChain, LangGraph, SmolAgents, Google ADK, CrewAI or similar agent frameworks.Practical knowledge of building autonomous and multi-agent systems.Experience implementing advanced reasoning patterns, planning strategies and tool-augmented AI workflows.Strong understanding of software architecture, API development, microservices and distributed systems.Experience with SQL, data preprocessing, ETL pipelines, feature engineering and large-scale data processing.Experience with CI/CD pipelines and DevOps practices.Knowledge of MLflow, Airflow or similar MLOps platforms.Strong analytical, communication, and problem-solving skills.Fluent English communication skills, both written and spoken.
Nice to Have:
Experience with Generative AI evaluation frameworks and observability platforms (LangSmith, Arize, Galileo, Phoenix, etc.).Experience fine-tuning open-source models and working with model serving frameworks.Knowledge of graph-based AI architectures and knowledge graphs.Experience implementing AI governance, guardrails, and Responsible AI practices.
What we offer:
Employment contractAdditional day off on the occasion of birthdays/namedaysMedical package and life insuranceBenefit platform - you choose what you benefit fromAccess to training platforms to improve your knowledgeI know Talent - training or money for referring friends to work 😊!Besides, with us you can count on access to our products and services at preferential terms and benefits, which you will read about below
