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Remote, mid-level AI role with broad full-stack and data requirements increases qualified applicant density and competition.
Requires deep ML, data-platform, and RAG/agent experience, so cross-industry transferability is limited and domain-sensitive.
Multiple mandatory technical stacks, production ML and data expertise, plus client-delivery experience make filters highly stringent.
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Own end-to-end delivery of AI-native full-stack applications including data foundation design, system architecture, development, and production deployment.
Design and build robust data infrastructure: models, schema, ETL/ELT pipelines, and manage data quality and slowly changing dimensions in production environments.
Leverage AI coding agents as a daily accelerator to rapidly ship production-grade AI systems, and lead orchestration and cloud deployment on AWS/Azure.
At least 5 years of professional experience with Python and full-stack AI product development.
Strong data engineering skills including advanced SQL, dimensional modeling, ETL/ELT pipelines, dbt experience, and modern cloud data platforms (e.g. Snowflake, Databricks).
Experience with FastAPI, Next.js, PostgreSQL, CI/CD, and cloud deployments on AWS or Azure.
Work Experience Required: Minimum 5 years in relevant data engineering and full-stack development roles.
Operates with full ownership from client discovery through production, bridging technical and business requirements effectively.
Proficient in AI-paired engineering workflows, using AI coding agents to significantly accelerate development without sacrificing quality.
Comfortable working in client-facing delivery roles and designing scalable, opinionated data systems and application architectures from scratch.