Senior Data Engineer (with AI)

• Design, build, and maintain robust data pipelines and ML systems for production environments
• Develop and deploy ML and LLM-based solutions addressing real client business challenges
• Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools
• Implement MLOps practices: CI/CD, automated testing, model monitoring, and experiment tracking
• Architect and implement cloud-native data and AI/ML solutions, primarily on AWS
• Collaborate closely with Data Scientists, AI/ML Engineers, Backend Engineers, and client stakeholders
• Participate in code reviews, contribute to technical documentation, and share knowledge within the team
• Engage in client-facing discussions to understand requirements and propose technical solutions

• 6+ years of hands-on engineering experience with production systems
• Full-stack mindset, comfortable across AI, Backend development, Data, and cloud infrastructure
• Autonomous working style
• Experience adopting AI tools in day-to-day workflows (e.g. Claude Code, GitHub Copilot, or similar)
• Strong sense of ownership and proactivity
• Openness to broadening skills into adjacent areas
• B2+ English, comfortable collaborating across distributed, multicultural teams
• Strong Python and SQL skills and solid software engineering fundamentals
• Hands-on experience with Apache Spark for large-scale data processing
• Proficiency with cloud data warehouse technologies: Snowflake, Redshift, or ClickHouse
• Proven experience building batch data workflows with Apache Airflow or similar orchestration tools
• Experience with real-time data processing using Kafka and streaming frameworks
• Experience with LLM-based application patterns, including RAG architectures, prompt design, and agentic workflows
• Basic understanding of embedding models, vector databases, and semantic search
• Awareness of LLM evaluation techniques and quality assurance approaches
• Experience deploying and maintaining ML models in production environments
• Understanding of CI/CD practices applied to ML pipelines
• Hands-on experience with AWS (SageMaker, Bedrock, Lambda, Glue, S3, ECR, or similar)
• GCP considered

Relevant cloud certifications are a plus

• Impactful work: projects span GenAI, MLOps, and NextGen data platforms for global enterprises across multiple industries
• Senior-calibre peers: collaborate with top ML and Data professionals across North America, LATAM, and EMEA
• Career growth: a clear path toward Tech Lead if you have the ambition — we actively develop our engineers
• Recognised expertise: AWS Premier Consulting Partner featured in Forrester’s AI Technical Services Landscape