Staff Software Engineer, Distributed Systems

Syllo

23d•$190,000 - $230,000•Remote

About The Position

Syllo is building a unified litigation platform that helps lawyers and paralegals use language models and agentic AI throughout the litigation life cycle. The company serves enterprise customers, including major law firms and corporations, and aims to reduce litigation costs and improve access to high-quality legal representation. The Staff Software Engineer will be a key member of Syllo’s new Systems team, which owns platforms, frameworks, tools, patterns, and architecture. The role combines hands-on technical design and implementation with helping foster a collaborative, high-performing environment where engineers can grow and learn. The position focuses on scalable cloud infrastructure, distributed systems, platform reliability, data pipelines, internal developer tools, and cloud data security.

Requirements

Core software engineering skills, including proficiency in languages such as Python and Ruby.
Strong system administration experience, including fluency with Linux, networking, and Bash scripting.
Proficiency with Google Cloud Platform (GCP).
Proficiency with cloud tools and distributed systems such as Kubernetes, Kafka, Postgres, and Elasticsearch, or equivalent technologies.
Demonstrated expertise in Infrastructure as Code using tools such as Terraform.
Ability to design and implement scalable, resilient cloud infrastructure.
Strong analytical and troubleshooting skills and a proactive approach to problem-solving.
Excellent communication and interpersonal skills, with the ability to engage effectively with technical and non-technical stakeholders.
Experience addressing scaling challenges and resource contention in distributed systems.
Expertise in cloud data security.

Nice To Haves

Engagement with the open-source community, including researching tools, reporting bugs, and contributing code.

Responsibilities

Design, implement, and manage scalable cloud-based infrastructure using Kubernetes, Pub/Sub, and other relevant technologies.
Collaborate with the AI team to optimize data pipelines and integrate AI technologies to remove performance bottlenecks.
Refactor systems to improve scalability, including converting stateful components to stateless ones and applying autoscaling and auto-repair mechanisms.
Lead data ingestion and export processes, improving efficiency and reducing dependencies on legacy technologies.
Drive platform reliability initiatives, including improving alerting, health checking, and incident management.
Champion continuous improvement, including cost control and technology upgrades.
Oversee development of internal tools that streamline workflows and reduce duplicated effort in development environments.
Ensure the platform meets testing and security standards to maintain data integrity and security.
Participate in an on-call rotation to ensure service-level agreements are met.