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# Software Engineer

- **Company:** ZEFR
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $180,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Code Review, Data Structures, Data Stores, Cursor (Graphical User Interface Elements), Distributed Systems, Elasticsearch, Python (Programming Language), PostgreSQL, Octopus Deploy, Software Engineering, Data Processing, Cloud Platform System, System Availability, Large Language Models, Snowflake, Pandas, Kubernetes, Information Technology, Dask, Apache Kafka, Api Design, Terraform, Docker, Microservices
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-zefr-8798457

## About the Role

* Bachelor's or Master's degree in Computer Science or related field with 5+ years of professional software engineering experience
 * Deep hands-on experience designing, building, running, and operating microservices in Kubernetes and cloud environments (GCP, AWS, or Azure)
 * Proficiency using AI for coding and research as a daily productivity multiplier (e.g., Claude Code, Copilot, Cursor)
 * Strong foundation in distributed systems, API design, data structures, algorithms, and software design
 * Thorough testing and code review standards/practices
 * Self-starter who identifies problems, proposes solutions, and drives them to completion with minimal direction
 * Strong collaboration skills and strong verbal and written communication skills
 * Big plus: proficiency with LLMs, MCP (Model Context Protocol), agent-gateway, and agentic infrastructure

## Description

We are hiring a Senior Software Engineer to own the design, implementation, and operation of microservices running in Kubernetes and other cloud-scalable, highly available environments. In this role you will build and run the production systems that power Zefr's platform at scale, and you will use AI fluently - for coding, research, and problem-solving - as a core part of how you work. Success in this position looks like a self-starter who takes ambiguous problems from design through production, operates what they build, and raises the engineering bar for the team through strong collaboration and clear communication.

 * Own the design and implementation of microservices, and run and operate them in Kubernetes and other cloud-scalable, highly available environments.
 * Design systems for scale, reliability, and high availability, and take accountability for the operational health of owned services, including observability, alerting, and incident response.
 * Use AI tools for coding and research as a daily part of the engineering workflow, and help the team adopt effective AI-assisted development practices.
 * Collaborate with product, ML, and infrastructure teams to translate requirements into robust technical designs.
 * Contribute to architectural decisions, design reviews, and engineering standards across the platform.
 * Mentor other engineers and communicate technical direction clearly to technical and non-technical stakeholders.

Languages: Python Data stores: Snowflake, Elastic Search, PostgreSQL Data processing: Apache Kafka, Dask, Pandas DevOps: Github Actions, Docker, Terraform, Kubernetes, ArgoCD, AWS/GCP


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