Senior AI Engineer

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field, or equivalent practical experience.
• 4+ years of professional software engineering experience, with strong experience developing enterprise applications using Java and Spring Boot.
• Strong experience designing and developing REST APIs and microservices.
• Hands-on experience with cloud-based application development, preferably on Google Cloud Platform (GCP).
• Practical experience with Apache Kafka or similar event-driven messaging technologies.
• Experience developing or integrating LLM/AI-powered applications and APIs in production or enterprise environments.
• Experience with machine translation, multilingual content processing, NLP, or related AI-driven content technologies.
• Strong understanding of software engineering practices, including Git, CI/CD, automated testing, code reviews, and Agile methodologies.
• Experience integrating applications with existing enterprise platforms, APIs, and third-party services.
• Ability to troubleshoot production issues and contribute to monitoring, logging, performance optimization, and operational support.
• Strong written and verbal English communication skills, with the ability to communicate effectively with technical teams and stakeholders.

• Experience with content-management, publishing, media, or digital content platforms.
• Experience working with LLM providers, AI APIs, or machine-translation platforms such as Google Cloud Translation, Azure AI Translator, AWS Translate, or equivalent services.
• Familiarity with Google Cloud Platform services such as GKE, Cloud Run, Pub/Sub, Cloud Storage, BigQuery, or similar.
• Experience with multilingual NLP, translation quality evaluation, language detection, or localization workflows.
• Familiarity with AI/LLM orchestration frameworks and tools such as LangChain, LangGraph, LangSmith, or equivalent.
• Experience implementing observability solutions using tools such as Cloud Monitoring, Cloud Logging, Datadog, Grafana, or equivalent.
• Experience with Docker and containerized application deployments.
• Experience working with high-volume, distributed, or latency-sensitive systems.
• Familiarity with media or publishing workflows, content pipelines, editorial systems, or international content distribution.
• AI Tooling Proficiency: comfort using AI tools to optimize day-to-day work, including development, analysis, research, testing, and automation, with the ability to identify opportunities to improve engineering workflows.

• Design, develop, and enhance scalable content and translation platforms using Java and Spring Boot, REST APIs, and microservices architectures.
• Build and integrate LLM- and AI-powered translation capabilities into enterprise content-processing workflows.
• Develop reliable APIs and backend services for translation requests, processing, and results, ensuring scalability, performance, and maintainability.
• Integrate with AI/LLM and machine-translation providers, evaluating opportunities to improve translation quality, scalability, cost, and latency.
• Design and implement event-driven architectures using technologies such as Apache Kafka to support high-volume content-processing pipelines.
• Integrate translation and content services with existing enterprise platforms, APIs, and downstream systems.
• Develop solutions for multilingual content processing, supporting multiple languages, content types, and international publishing requirements.
• Implement robust error handling, retries, monitoring, logging, alerting, and other operational capabilities required for reliable production systems.
• Develop automated tests and validation mechanisms to ensure the quality and reliability of translation workflows and services.
• Contribute to performance and scalability improvements as content and translation volumes increase.
• Support production deployments, troubleshooting, incident resolution, and ongoing operational improvements.
• Collaborate closely with engineering, product, and client stakeholders to define technical solutions, participate in design discussions, and translate business requirements into scalable software.
• Contribute to technical documentation, code reviews, CI/CD practices, and engineering standards.
• Help evolve the platform architecture to support future international expansion, additional languages, and new content types.
• Stay current with developments in GenAI, LLMs, machine translation, multilingual NLP, cloud technologies, and distributed systems, applying relevant practices to production solutions.

Sounds awesome, right? Now, let's make sure you're a good fit for the role: