Principal Software Developer – AI Data Architect
New
This is a fully remote position located in Colombia.Full-TimePrincipal
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 10+ years of experience in software development and data engineering, with at least 5 years in a senior technical leadership role
- Required Skills
- AWSPythonSQLKafkaData engineeringSpark
Requirements
- 10+ years of experience in software development and data engineering.
- At least 5 years in a senior technical leadership role, such as Principal Developer or Data Architect.
- Hands-on experience architecting data for AI workflows: embedding pipelines, vector-based retrieval, RAG, and real-time event-driven flows.
- Proficiency with AI platform integration patterns, agent orchestration, and LLM observability (e.g., LangGraph, Langfuse).
- Expertise in designing modern cloud-native data platforms on AWS, including lakehouse patterns, medallion architecture, and distributed processing (Spark, Trino).
- Deep knowledge of data technologies: MongoDB, DocumentDB, SQL Server, DynamoDB, Redis/Valkey, and Kafka/PubSub.
- Expertise in AWS data services: S3, Athena, Glue, Lake Formation, OpenSearch, Iceberg, EKS, and Lambda.
- Experience with CI/CD, infrastructure-as-code, and DevOps operational practices.
- Strong English language communication and collaboration skills.
Responsibilities
- Define and execute the technical strategy for a scalable AI-Ready data platform.
- Create and evolve reference architectures, modeling standards, and best practices for ingestion, normalization, and AI interoperability.
- Contribute to key platform projects including data layer re-architecture and schema modernization.
- Mentor developers, fostering a mentorship culture and ensuring adherence to high standards in data engineering.
- Collaborate with R&D and Security teams to implement data contracts and define data classification, governance, and access controls.
- Define and implement standards for data quality, lineage, and observability to ensure audit-ready datasets.
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