Senior Python Engineer – AI Agents, LLM Systems

📋 Description

• Designing and executing AI solutions that align with business requirements and technological standards.

• Utilizing methods such as Retrieval-Augmented Generation (RAG) to enhance the accuracy and relevance of AI interactions.

• Developing Agentic RAGs that integrate autonomous agents to optimize data retrieval and content generation.

• Creating modular frameworks for agents focused on tasks such as information retrieval, contextual understanding, and data-driven decision-making.

• Utilizing Large Language Models (LLMs) like Gemini and Llama for text generation and question answering.

• Designing and overseeing data ingestion workflows, implementing serverless architectures and Pub/Sub models to scale data intake.

• Employing DevOps and MLOps methodologies to automate the deployment and management of AI models.

• Integrating APIs to link AI models with external systems and to log events and metadata.

• Enhancing performance by analyzing system efficiency, identifying bottlenecks, and applying caching strategies.

• Collaborating with designers and product teams to ensure AI solutions address genuine business and user needs while fostering innovation through ongoing research and experimentation.

⛳️ Requirements

• Advanced skills in Python development.

• Demonstrated experience with Hybrid AI / RAG architectures and cutting-edge LLMs (commercial: OpenAI, Gemini; open-source: Llama 2, Mistral).

• Practical experience with orchestration frameworks such as LangChain, LlamaIndex, Rasa, or Haystack.

• Strong grasp of classical Machine Learning for predictions and anomaly detection.

• Experience with Docker, Linux, and hybrid cloud environments (Azure, GCP), including on-premises deployments.

• Proficiency in SQL and NoSQL databases, with an emphasis on optimization and data retrieval for RAG and model pipelines.

• Solid background in API design and integration (REST), encompassing data anonymization/encryption, authentication, and access control.

• Familiarity with MLOps tools and practices (Git/GitHub, MLflow or equivalents) for versioning, tracking, and monitoring models.

• Understanding of data quality, governance, and reporting (KPIs) within AI solutions.

• Experience with Azure Databricks for scalable data processing, model training, and deployment workflows (ETL, Spark, Delta Lake, MLflow integration).

• Experience with Azure Purview for data cataloging, governance, lineage, and ensuring compliance (GDPR, data classification, policies).

• Excellent collaboration abilities and a knack for delivering prompt, impactful solutions across teams.

• (Nice to have) Experience in RPA and process automation, e.g., Power Automate.

🏝️ Benefits

• Remote work.

• Flexible hours.

• Special timetable: 7 hours on Fridays and during summer.

• Individual budget for attending forums and training.

• English classes.

• Health insurance.

• Every three years, 6 additional days off.

• Day off on your birthday.

• Refer a friend and benefit from it.

• Flexible compensation options.

• Wellness program - Gympass.

• Volunteering opportunities.

• Company events and team building activities.