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# Senior Software Engineer

- **Company:** Intentsify, LLC
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Business Logic, Batch Processing, Code Review, Continuous Integration, Extract Transform Load (ETL), Identity and Access Management, Python (Programming Language), Machine Learning, Amazon Simple Notification Service (SNS), SQL Databases, Pulumi, Data Processing, Large Language Models, Snowflake, Event Driven Architecture, Amazon Simple Queue Service (SQS), Terraform, Docker
- **Published:** September 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6d89a533339b416c

## About the Role

* Senior-level experience: years of building and operating production systems, comfortable owning products end to end with limited supervision.
 * Strong Python skills in both data-processing and service/API contexts.
 * SQL and cloud data warehousing (Snowflake or equivalent), with a healthy instinct for data correctness and idempotency.
 * Event-driven architecture on AWS (SQS/SNS, S3, IAM, Secrets Manager), with workloads running in Docker and Kubernetes.
 * Experience with a workflow orchestrator (Argo Workflows, Airflow, Dagster, or similar).
 * Operational maturity: you instrument what you build and can diagnose a production issue yourself.
 * Effective in a small cross-functional team, and able to explain technical tradeoffs to data science and product stakeholders.

Nice to have:

 * Infrastructure as code (Pulumi or Terraform).
 * Serving ML models in production: transformer inference, vector databases, GPU scheduling, and LLM APIs.

## Description

* Own processes end to end - design, implement, test, deploy, monitor, and support them in production.
 * Build and maintain ETL pipelines: scheduled and event-driven batch processing over large volumes of web, behavioral, and account data.
 * Own the team's infrastructure, CI/CD, and observability, including consolidating older systems onto the current platform.
 * Be accountable for the correctness of the data your systems produce; silent data issues matter as much as outages.
 * Make key technical decisions, write tests that exercise real business logic, and give substantive code reviews.

How we work:

 * Small teams, high autonomy. Teams are 2-4 engineers and own their services and optionally their infrastructure.
 * Ship fast, iterate often.
 * Prefer the simpler solution for MVPs; be skeptical of premature abstraction.
 * Direct ownership of production. You deploy your own work, you see it run, and you fix it when it breaks.


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