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Staff Engineer - Contract

Posted 2 days agoViewed

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📍 Location: United Kingdom

🔍 Industry: Software Development

🏢 Company: Memrise👥 51-100💰 $15,500,000 Series B over 6 years agoEducationEdTechE-LearningSoftwareLanguage Learning

🗣️ Languages: English

Requirements:
  • Proficiency in Java or preferably Kotlin
  • Strong experience with event-driven architectures and Kafka, with a preference for Kafka Streams.
  • Expertise in AWS infrastructure, including the ability to write Terraform and deploy scalable, secure, resilient services.
  • Strong proficiency in containerization (Docker) and orchestration technologies like Kubernetes.
  • Strong experience with data pipelines and analytics, with the ability to design, implement, and optimise solutions. Knowledge of technologies such as Kafka events, Athena, and similar tools is highly valued
  • Proven ability to design and build microservices from scratch, with experience using LLMs and AI-powered tools to accelerate development and reduce manual effort.
  • Experience in LLMs (Large Language Models) and AI-driven automation to improve development workflows, streamline coding, and optimize infrastructure management.
  • Passion for leveraging AI-powered tools to optimise CI/CD pipelines, automate infrastructure management, and improve operational efficiency.
  • Demonstrated leadership in guiding and mentoring engineering teams, fostering a culture of AI-assisted development and DevOps best practices.
  • Strong communication and collaboration skills, fostering cross-functional partnerships across product, engineering, and operations teams.
Responsibilities:
  • Collaborating directly with our DevOps engineer to implement best practices, optimise workflows, and actively participate in solving infrastructure challenges.
  • Making complex DevOps and backend processes easy to understand.
  • Ensuring the team gains confidence in backend and infrastructure development.
  • Assessing how things can be done more efficiently and using AI to reduce manual effort.
  • Introducing AI-driven tools and methodologies to improve productivity, while mentoring engineers who are still building confidence in these areas.
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