GRADION

Backend Engineer

• Architect & Build: Design and implement high-throughput microservices using FastAPI and Python 3.12+.
• Optimize Communication: Lead the integration of gRPC protocols to facilitate low-latency, high-performance service-to-service communication.
• Scale Microservices: Own the lifecycle of services within a distributed architecture, from initial design to containerization and deployment.
• Bridge the Stack: While primarily backend-focused, you will occasionally collaborate on or build out intuitive interfaces using Vue.js.
• Technical Leadership: Conduct rigorous code reviews, mentor mid-level engineers, and champion best practices in CI/CD and automated testing.
• Hybrid Collaboration: Work closely with product teams in a hybrid capacity, balancing focused deep-work days with high-energy in-office brainstorming.

Senior Python Engineer

Data Engineer

• Advise senior client stakeholders on modern data architecture, cloud migration strategies, and the secure, compliant use of data for business value.
• Define clear roadmaps for clients to transition from legacy data warehouses to scalable cloud-native data platforms (e.g., Data Lakes, Lakehouses).
• Design data pipelines and structures that enable clients to monetize data assets and derive actionable insights.
• Conduct data maturity assessments and define target-state architectures and roadmaps.
• Communicate complex data and AI topics in clear business language to executives and stakeholders.
• Lead the design and implementation of robust, scalable, and cost-efficient data infrastructure (data lakehouse, data mesh, or centralized warehouse) on major hyperscaler platforms (AWS, Azure, GCP).
• Develop and optimize high-throughput data pipelines using modern ELT/ETL tools (e.g., Spark, Flink, Kafka) to handle large data volumes and integrate disparate data sources.
• Build, deploy, and manage production-ready machine learning AI/ML pipelines (MLOps) including feature stores, ML model registries, model training, workflows (e.g., MLflow, Vertex AI, SageMaker, Azure ML), serving and monitoring.
• Explore and implement data engineering infrastructure required to develop and deploy Small Language Models and other applied AI solutions within client environments for specific client use cases.
• Establish data governance, lineage, and compliance controls to ensure trustworthy AI and regulatory readiness.
• Contribute to Gradion’s internal frameworks for data platform modernization and AI readiness.
• Define and implement data governance frameworks aligned with ISO, FINMA, GDPR, or MedTech requirements.
• Embed data security, masking, and access control into pipelines and platform layers.
• Help clients design policy-as-code and automated compliance guardrails for data and AI systems.
• Conduct technical and architectural assessments (data platform Health Checks) to identify bottlenecks, security gaps, and cost inefficiencies.

Senior Python Engineer

Senior Consultant – Data Engineering