Senior Software Developer, AI Data Engineer
New
C
CasewareFintech, SaaS
This is a fully remote position located in Colombia.Full-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Strong English language communication and collaboration skills.
- Required Skills
- AWSPythonTypeScriptNest.jsTerraformCloudFormationDistributed Systems
Requirements
- Strong software engineering fundamentals, including designing maintainable, testable systems and owning features end-to-end.
- Production experience with distributed systems, including async workflows, failure modes, retries, and eventual consistency.
- Hands-on experience building and operating data pipelines for AI systems, such as embeddings pipelines, retrieval workflows, or feedback data processing.
- Experience working with AI-related data infrastructure, including vector databases, search systems, or graph-based storage.
- Experience with retrieval systems (RAG), embedding pipelines, or hybrid search.
- Experience with agent frameworks, agent memory systems, or orchestration of tool-using AI systems.
- Experience operating production systems, including monitoring, incident response, and continuous improvement.
- Cloud experience on AWS building production systems, including storage, messaging, and orchestration.
- Experience with infrastructure as code, with CDK preferred and CloudFormation or Terraform acceptable.
- Strong collaboration and communication skills, with the ability to mentor.
- Strong English language communication and collaboration skills.
Responsibilities
- Design and implement reliable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured, and multi-modal data.
- Build and scale retrieval infrastructure, including vector storage, embedding pipelines, hybrid search, and graph-based knowledge representations.
- Develop and operate agent memory systems and pipelines for AI system signals to support observability and continuous improvement.
- Apply data quality, validation, monitoring, and testing frameworks in production pipelines.
- Monitor, troubleshoot, and optimize AI data pipelines and retrieval workflows for reliability, performance, and cost.
- Design and support evaluation workflows for AI systems, enabling offline testing and benchmarking.
- Lead pragmatic platform evolution by defining clear contracts between AI services and data systems.
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