Platform Engineer İş İlanı

About the Role We're looking for a Senior Engineer to join our Platform team and shape the internal tooling that empowers engineering teams across the organization. You'll design, build, and maintain high-impact developer tools — including CLI applications for environment setup, CI/CD modernization frameworks, data access libraries, and self-service platform capabilities — that directly accelerate how our engineers ship software. What You'll Work Tooling & Developer Experience: Build and evolve applications that streamline environment provisioning, configuration, and day-to-day developer workflows. CI/CD Modernization: Design and implement next-generation continuous integration and delivery pipelines, driving adoption of modern GitOps workflows and reliable deployment practices. Data Access Libraries & SDKs: Develop internal libraries that provide consistent, secure, and performant access to data stores — abstracting complexity away from consuming teams. Internal Tooling & Automation: Identify repetitive pain points across engineering and build robust, 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 — from architecture and prototyping through testing, development, and support. Drive modern software engineering practices through code and design reviews; champion DevOps principles for continuous delivery with high-quality telemetry. Evaluate emerging technologies through proof-of-concept work and recommend adoption where they fit our platform needs. Lead design discussions and align teams on architectural and strategic decisions for shared platform components. Mentor junior engineers through coaching, pairing, and thoughtful code/design reviews. AI Proficienciency Proficient in integrating AI coding assistants, CLIs, and Model Context Protocols (MCPs) into daily development workflows. Uses AI effectively across the software development lifecycle — planning, design, implementation, debugging, deployment, and observability. Builds reusable AI tooling (agent rules, skills, internal MCPs) that compounds team productivity, while applying judgment about when AI is and isn't the right tool. Balances AI-driven velocity with engineering rigor — implements automated testing, structural guardrails, and CI mechanisms to validate AI-generated code and prevent technical debt. What We're Looking For Required Experience: 4–8 years of professional software engineering experience building production systems at scale. Education: Bachelor's degree or higher in Computer Science, Engineering, or a related field. Python Mastery: Deep proficiency in Python — strong grasp of OOP, design patterns, packaging, dependency management, and building maintainable libraries and CLI tools(good to have). Software Architecture: Demonstrated ability to design well-structured, loosely coupled systems. Comfort making trade-offs between simplicity, extensibility, and performance. Cloud & Infrastructure: Hands-on experience with cloud platforms (Azure, AWS, or GCP). Container Orchestration & CI/CD: Experience with Docker, Kubernetes, and building CI/CD pipelines (GitHub Actions, Jenkins, or similar). Exposure to GitOps workflows (Flux, ArgoCD) is a plus. Data Access & Storage: Experience working with relational databases (PostgreSQL, MSSQL) and NoSQL/key-value stores. 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. Core Competency ● Judgment: Sound decision-making with incomplete information; ability to evaluate trade-offs between cost, reliability, performance, and developer experience. ● Ownership: End-to-end accountability from problem identification through solution delivery and adoption. ● Collaboration: Clear communication across teams and geographies; empathy for internal users; effective remote collaboration. ● Initiative: Proactive identification of workflow bottlenecks and a drive to eliminate them through thoughtful tooling.