Staff Engineer

• The role: Staff Engineer

• Salary: up to 37 500 PLN/month

• Type of contract: UoP

• Working model: Remote

Join our client, which makes software to help users organize data, discover the truth, and act on it. Their SaaS product manages large volumes of data and quickly identifies key issues during litigation and internal investigations. The AI-powered communication surveillance product proactively detects regulatory misconduct like insider trading, collusion, and other non-compliant behavior. They have over 300,000 users in 49 countries serving thousands of organizations globally.

As a Staff Software Engineer on the Compute team, you will lead the design and development of a next-generation compute platform that powers scalable workloads. Your focus will be on creating robust, event-driven, and batch-capable compute infrastructure using Kubernetes, KEDA, Temporal, Apache Spark, and advanced stream processing technologies.

You will be part of an Infrastructure Services organization, structured into specialized teams focused on core platform areas such as compute, networking, and storage. The Compute team enables developers to deploy scalable workloads—from microservices and scheduled jobs to real-time data pipelines—leveraging cloud-native patterns that prioritize performance, elasticity, and developer autonomy.

Key Responsibilities:

• Architect and implement cloud-native compute solutions to orchestrate background jobs, long-running workflows, and streaming data pipelines.

• Develop and maintain compute abstractions integrating Kubernetes, KEDA, and Temporal to support scalable job and service orchestration.

• Lead development of elastic data processing approaches using Apache Spark for batch workloads and streaming frameworks for real-time analytics.

• Define and promote best practices for running event-driven and parallel workloads in production environments.

• Collaborate with engineering teams to support various compute use cases, including microservices, cron jobs, ETL, workflow engines, and machine learning workloads.

• Ensure reliable autoscaling, failure handling, and resource optimization across compute workloads.

• Partner with platform security and observability teams to ensure compliance, transparency, and monitoring of workload execution.

• Mentor engineers on distributed system design and modern compute orchestration techniques.

Minimum Qualifications:

• 8+ years of experience in backend, infrastructure, or data platform engineering roles.

• Extensive production experience with Kubernetes (preferably AKS).

• Hands-on experience with orchestration/eventing frameworks like KEDA, Temporal, or similar.

• Skilled in developing batch (e.g., Spark) and streaming (e.g., Kafka, Flink, Azure Event Hubs) processing systems.

• Strong programming skills in Go, Python, or C#, focusing on distributed or event-driven systems.

• Familiarity with secure compute design, autoscaling, and high-availability architectures.

Preferred Qualifications:

• Experience implementing KEDA, Temporal, or Argo Workflows in production environments.

• Knowledge of Azure Synapse, Azure Data Explorer, Azure Data Factory, or Databricks.

• Experience building compute platforms for streaming analytics, ETL pipelines, or AI/ML workloads.

• Understanding of event-driven and pub-sub architectures like Kafka or Azure Event Grid.

• Contributions to cloud-native or CNCF open-source projects.

Leadership Expectations:

• Define the strategy and technical roadmap for a unified compute platform.

• Promote cloud-native, event-driven, and scalable architecture practices across teams.

• Lead architecture reviews and encourage adoption of modern orchestration technologies.

• Mentor engineers and lead teams toward resilient, observable, and developer-friendly compute solutions.

• Drive long-term initiatives to improve workload performance, efficiency, and maintainability.

Core Competencies:

• Cloud-Native Orchestration: Expert knowledge of Kubernetes-based job orchestration and scalable compute architectures.

• Data Processing: Ability to design for hybrid streaming and batch workloads in modern applications.

• Technical Leadership: Influences platform strategy and architectural direction organization-wide.

• Scalable System Design: Proven track record of scaling compute across diverse workloads and tenants.

• Developer Experience: Passionate about empowering engineering teams with powerful yet easy-to-use platforms.

Benefit Highlights:

• Comprehensive health, dental, and vision plans

• Parental leave for primary and secondary caregivers

• Flexible work arrangements

• Two, week-long company breaks per year

• Unlimited time off

• Long-term incentive program

• Training investment program