{"id":69434,"url":"https://alion.io/job/appier-senior-software-engineer-backend-developmentad-cloud-serving-services","title":"Senior Software Engineer, Backend Development(Ad Cloud Serving Services)","company":{"id":177717,"name":"Appier","domain":"appier.com","url":"https://alion.io/company/appier-2","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":86,"open_postings":59,"ghost_share":0.153,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":323,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taipei, Taiwan"],"countries":["TW"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ClickHouse","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"gRPC","optional":false},{"name":"Incident Management","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"MySQL","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"SQL","optional":false},{"name":"A/B Testing","optional":true},{"name":"Machine Learning","optional":true},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2025-07-03T02:58:14Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-10-26T18:14:07Z","board_verified":true,"closed_at":null,"days_open":480,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":480},"description":"About Appier \nAppier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud-each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.\nAbout Ad Cloud Serving Services Team\nAt Appier's Ad Cloud Team Serving Services Team, we build and maintain the critical systems that power the core of Appier's advertising technology. These systems handle massive, high-concurrency, real-time requests, and ensure the stability, low latency, and high performance of our ad delivery. Our SRE professionals are crucial in guaranteeing these services remain reliable under extreme loads, continuously enhancing product availability and performance through innovation and automation.\nResponsibilities\nLead the design and development of scalable, high-performance, and reliable backend services for real-time ad recommendation, data serving, and core ad tech infrastructure.\nDrive technical roadmap and ownership for sizable projects, ensuring the delivery of robust and efficient solutions within the Ad Cloud ecosystem.\n Optimize critical system components for latency, throughput, and resource utilization, including database interactions (e.g., MongoDB sharding, ClickHouse optimizations) and network architecture.\n Enhance system observability, incident management, and operational excellence by implementing comprehensive monitoring, alerting (e.g., Grafana, Prometheus), and refining production SOPs.\nCollaborate closely with product managers and scientists to translate business requirements into technical designs and ensure seamless integration.\nChampion code quality through rigorous code reviews and adherence to best practices in system design and implementation.\nMentor and guide junior engineers, fostering their growth in backend development best practices, distributed systems, and agile methodologies.\nActively participate in on-call rotation within the Backend team to maintain product reliability and scalability for critical serving services.\nContribute to a culture of continuous improvement, initiating team-level technical discussions, process enhancements, and knowledge sharing.\nAbout You\n[Minimum Qualifications]\n3-5+ years of hands-on experience in backend software development, particularly with high-performance, high-concurrency systems.\nProficient in one or more of the following languages: Go, Python.\nStrong experience in system design and architecture for scalable and distributed systems, especially within a Linux environment.\nGood understanding of Network API Design (e.g., RESTful APIs, gRPC) and experience with message queues (e.g., Kafka, Pub/Sub) for data pipelines.\nSolid knowledge of SQL/NoSQL databases (e.g., MySQL, MongoDB, Redis, ClickHouse, PostgreSQL) and experience with database optimization and scaling strategies.\nFamiliarity with DevOps practices, including CI/CD pipelines, Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).\nExperience with observability tools (e.g., Prometheus, Grafana) and robust monitoring and alerting implementation.\nProactive, excellent problem-solving skills, and strong communication in a cross-functional team setting.\n[Preferred Qualifications]\nBS/MS degree in Computer Science or a related field.\nDemonstrated ability to refactor complex systems, improve performance metrics (e.g., latency, error rate, CPU usage), and optimize resource utilization.\nFamiliarity with A/B testing frameworks and supporting customizable configurations for model iteration.\nHands-on 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