Senior Software Engineer

Senior Software Engineer – Internal Developer Tooling

Location: Krakow, Poland or Sofia, Bulgaria

Function: Platform Engineering / Developer Tooling Level: Senior (4–8 years)

We're hiring a Senior Software Engineer to join a Platform team building the internal tooling that empowers engineering teams across the organization. You'll design, build, and maintain high-impact developer tools — CLI applications for environment setup, CI/CD modernization frameworks, data access libraries, and self-service platform capabilities — that directly accelerate how engineers ship software.

This is a hands-on role where architecture instincts matter as much as writing clean code. You'll own tools end-to-end: from spotting friction in developer workflows, through design and build, to adoption and ongoing support.

What You'll Work On

• Tooling & Developer Experience: Build and evolve applications that streamline environment provisioning, configuration, and everyday developer workflows.
• CI/CD Modernization: Design next-generation CI/CD pipelines and drive adoption of modern GitOps workflows and reliable deployment practices.
• Data Access Libraries & SDKs: Develop internal libraries providing consistent, secure, performant access to data stores — abstracting complexity away from consuming teams.
• Internal Tooling & Automation: Identify repetitive pain points across engineering and build reusable tooling to eliminate them.

Responsibilities

• Architect and deliver internal tools and libraries that are well-defined, modular, secure, scalable, and actively maintained.
• Contribute across the full development lifecycle — architecture, prototyping, testing, development, and support.
• Drive modern engineering practices through code and design reviews; champion DevOps principles and high-quality telemetry.
• Evaluate emerging technologies through proof-of-concept work and recommend adoption where they fit.
• Lead design discussions and align teams on architectural decisions for shared platform components.
• Mentor junior engineers through coaching, pairing, and code/design reviews.

AI Proficiency

• Proficient integrating AI coding assistants, CLIs, and MCPs into daily development workflows.
• Uses AI effectively across the SDLC — planning, design, implementation, debugging, deployment, and observability.
• Builds reusable AI tooling (agent rules, skills, internal MCPs) that compounds team productivity, with sound judgment on when AI is (and isn't) the right tool.
• Balances AI-driven velocity with engineering rigor — automated testing, structural guardrails, and CI checks to validate AI-generated code.

What We're Looking For

Required

• 4–8 years of professional software engineering experience building production systems at scale.
• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• Deep proficiency in Python — OOP, design patterns, packaging, dependency management, and building maintainable libraries and CLI tools.
• Demonstrated ability to design well-structured, loosely coupled systems and make trade-offs between simplicity, extensibility, and performance.
• Hands-on experience with cloud platforms (Azure, AWS, or GCP).
• Experience with Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Jenkins, or similar); exposure to GitOps (Flux, ArgoCD) is a plus.
• Experience with relational databases (PostgreSQL, MSSQL) and NoSQL/key-value stores, with the ability to design clean data access abstractions.

Strongly Preferred

• Experience building internal developer tools, platform SDKs, or CLI frameworks.
• Experience with data platform technologies (Spark, PySpark, Databricks, Airflow, or Dagster).
• Exposure to modern data architectures (Delta Lake, Iceberg, data catalogs).
• Hands-on experience with observability tooling (Datadog, Grafana/Prometheus, OpenTelemetry, Statsig).
• Track record of driving developer adoption of platform tools and improving engineering productivity.

Tech Environment

Cloud: Azure (primary), AWS | Orchestration: Kubernetes | Data Platforms: Spark, Databricks, PySpark | IaC: Terraform | Observability: Datadog, Grafana/Prometheus | CI/CD: GitHub Actions | Languages: Python (primary)

NB: We value strong fundamentals and adaptability over specific tool expertise