Principal Software Developer – AI Data Architect
Lead the design and implementation of a next-generation data platform engineered for artificial intelligence. In this role, you will shape the architectural foundation that powers AI-driven analytics, secure data exchange, and intelligent automation across products. Your work will directly influence how data is structured, governed, and made accessible for machine learning and agentic systems at scale.
Key Responsibilities
- Define and drive the technical roadmap for a cloud-native, AI-Ready data platform, establishing patterns for scalability, reliability, and real-time data processing.
- Develop reference architectures and modeling standards, including medallion and lakehouse designs, to support ingestion, normalization, and AI interoperability.
- Lead data model modernization efforts across core products, guiding schema evolution and data layer re-architecture initiatives.
- Mentor engineering teams on data engineering best practices, ensuring consistency in data quality, modeling, and platform design.
- Collaborate with R&D to implement data contracts, standardize pipelines, and promote reuse across data products.
- Partner with security and compliance teams to enforce data classification, tenant isolation, access controls, and retention policies.
- Enable platform adoption by delivering reusable blueprints and reference implementations for common data workflows.
- Architect data observability into the platform, defining standards for lineage, freshness monitoring, alerting, and auditability.
Qualifications
You bring 10+ years of software and data engineering experience, with at least five in a senior technical leadership role. You have successfully architected production systems that support AI workflows, including vector retrieval, RAG pipelines, and event-driven data flows. Experience with cloud-native data platforms on AWS is essential, including services such as S3, Glue, Lake Formation, EMR, Lambda, and OpenSearch.
Deep familiarity with distributed data systems—Spark, Trino, Iceberg, DynamoDB, MongoDB, and Redis—is required, along with hands-on work in ETL/ELT, CDC, and event sourcing. You’ve implemented secure, multi-tenant data architectures and governed access patterns for customer-facing AI integrations.
You’ve led data governance initiatives, defined platform-wide standards, and worked closely with data science teams to operationalize AI-ready datasets. Proficiency in infrastructure-as-code, CI/CD, and DevOps practices ensures resilient, scalable delivery.
Strong communication skills are essential for aligning technical strategy across teams and advising leadership on architectural trade-offs. Fluency in English is required.
Preferred Knowledge
- LangGraph, Langfuse, MCP, AWS Bedrock, AWS AgentCore, LaunchDarkly
- Kafka or Pub/Sub, LLM proxy layers, Aurora PostgreSQL, pgvector
Benefits
- Indefinite employment contract with full legal benefits
- Prepaid medical coverage
- Life and funeral insurance
- Internet and home office allowances
- Competitive, above-market compensation
- 100% remote work with strong support for work-life balance
