{"id":1186771,"url":"https://alion.io/job/shopee-expert-backend-engineer-llm-big-data-product-application-data-infra-team","title":"Expert Backend Engineer (LLM, Big Data Product Application) - Data Infra Team","company":{"id":49909,"name":"Shopee","domain":"shopee.com","url":"https://alion.io/company/shopee","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"A","score":100,"open_postings":20,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":8,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":62000,"max_usd":130000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"ClickHouse","optional":false},{"name":"Flink","optional":false},{"name":"Function Calling","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Presto","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"StarRocks","optional":false},{"name":"Tool Use","optional":false},{"name":"Trino","optional":false},{"name":"Copilot","optional":true}],"status":"live","first_seen_at":"2026-09-24T15:03:08Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-20T23:47:14Z","board_verified":true,"closed_at":null,"days_open":26,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":26},"description":"Own the architecture, development, and productionization of core AI data product capabilities, including natural language to SQL, dashboard generation, and insight / report generation.\nBuild production-grade LLM application pipelines for enterprise data scenarios, including:metadata and schema retrieval\nsemantic layer and metric understanding\nquery planning and SQL generation\nSQL validation, rewriting, and execution\nvisualization spec generation\nnarrative insight generation\n\nDesign and implement reliable backend services and platform capabilities that balance accuracy, access control, explainability, observability, latency, and cost.\nDeeply understand user workflows in analytics and data consumption, and translate ambiguous business questions into scalable, reusable engineering systems.\nWork closely with Data Infra, Data Engineering, BI, Frontend, Design, and AI / ML engineering teams to deliver products from zero to one and scale them from one to many.\nEstablish and continuously improve the LLM evaluation and feedback loop, including offline benchmarks, online metrics, user feedback, prompt / model versioning, failure analysis, and quality improvement.\nDrive performance, reliability, and engineering excellence across the system, and contribute to long-term architectural evolution.\nStay current with best practices in LLM applications, AI agents, semantic analytics, and enterprise AI systems, and turn them into practical production solutions.\nBachelor’s Degree or above in Computer Science, Software Engineering, Data Engineering, or related fields.\nMinimum 6 years of experience in backend engineering, platform engineering, data infrastructure, or AI application engineering, with the ability to own complex system design and core module delivery.\nStrong computer science fundamentals, including data structures and algorithms, operating systems, networking, databases, and distributed systems.\nProficient in at least one backend language such as Go, Java, or Python.\nStrong hands-on experience building LLM-powered applications, with solid understanding of Prompt Engineering, RAG, Tool Calling, Agents, evaluation frameworks, inference optimization, and guardrails.\nStrong understanding of data and analytics products, including SQL, data modeling, data warehouses / lakehouses, OLAP systems, semantic layers, metrics systems, dashboards, and reporting.\nFamiliarity with one or more enterprise data / big data technologies such as Spark, Flink, Kafka, Trino / Presto, StarRocks, ClickHouse, Hive, or similar systems.\nStrong problem-solving and abstraction skills, with the ability to convert ambiguous requirements into robust and extensible technical designs.\nStrong product sense and user empathy; 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