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Responsible for core services of the Search/Recommendation system, including recall, ranking, and feature services.Design and build high-concurrency, high-availability architectures to improve system stability.Develop user feature systems to enable real-time game recommendations and collaborate closely with the algorithm team.Lead search product development to improve user search conversion rates.

About BTSE: BTSE Group is a global leader in fintech and blockchain technology, anchored by threecore business pillars: Exchange, Payments, and Infrastructure Development. Servingover 100 corporate clients worldwide, we provide white-label exchange and paymentsolutions. Our offerings encompass everything from exchange infrastructure hostingand development to custody, wallets, payments, blockchain integration, trading, andmore.We are looking for talented professionals in marketing, operations, customer support,and other departments. The roles offered may be on-site, remote, or hybrid, incollaboration with our local partner. About the opportunity: We're building an AI-powered research platform for institutional investors. Our platform turns vast amounts of market, alternative, and proprietary data into actionable intelligence — powered by AI agents that depend on clean, reliable, real-time data to do their job. We need someone to own data. Not manage a team that does data. Own it — from finding the right sources, to getting them flowing, to making sure they stay healthy at scale. Today we ingest from hundreds of sources. That number is growing fast. The sources are diverse: real-time market feeds, regulatory filings, on-chain blockchain data, news, social sentiment, alternative datasets, and proprietary client data. Some are free APIs. Some are $10K/month enterprise contracts. Some are clients pushing their own data into our platform. Every one of them is different, and most of them will break in ways you don't expect. You'll evaluate vendors, negotiate deals, build integrations, monitor quality, track costs, and make the call on what's worth paying for. When something breaks at 2 AM, you'll know why before the alert finishes firing. This is an end-to-end ownership role. No handoffs.ResponsibilitiesBuild and maintain integrations with a large and growing number of external data sources — APIs, WebSockets, file drops, streams, scrapers, and formats you haven't seen yet Evaluate and compare data vendors across quality, reliability, coverage, cost, and terms of service Negotiate contracts and manage commercial relationships with data providers Design and operate high-throughput ingestion pipelines handling mixed workloads (real-time, near-real-time, batch, event-driven) Build monitoring that tells you — before anyone else — when data is late, wrong, incomplete, or drifting Manage data quality at scale: anomaly detection, cross-source validation, schema drift detection, gap filling Handle both structured data (time-series, tabular) and unstructured data (documents, text, images) with appropriate extraction and storage Track costs per source, usage per consumer, and ROI — recommend what to keep, upgrade, or cancel Build tooling that makes adding the next data source faster than the last one Use AI tools aggressively in your daily work — for code generation, testing, documentation, anomaly analysis, and anything else that makes you fasterRequirements**You've done this before:**- 5+ years building data pipelines that run in production, 24/7, with real SLAs- Deep hands-on experience with SQL databases and time-series data- Python as your primary language, comfortable with async programming- You've integrated with dozens of external APIs and dealt with the reality of unreliable vendors, changing schemas, rate limits, and bad documentation- You've built monitoring and alerting for data systems — not as an afterthought but as part of how you work **You think about the whole picture:**- You don't just connect to an API. You think about what happens when it goes down, when the schema changes, when the data is wrong, when the bill doubles- You understand that data has a cost and a value, and not every source is worth keeping- You've worked with data vendors commercially — contracts, pricing tiers, usage negotiations **You use AI daily:**- AI coding tools are part of your workflow today, not something you're curious about- You can articulate specifically how AI makes you faster and where it doesn't help- You'd be frustrated if you couldn't use AI in your workNice to haveExperience with financial or crypto market data Experience with streaming systems (Kafka or similar) at scale Vector database or embedding pipeline experience Experience with unstructured data extraction (PDFs, documents, NLP)Perks BenefitsSenior individual contributor role with full ownership of the data domain Direct access to leadership — no bureaucracy, fast decisions AI tools provided and encouraged across all work Remote-friendly, async-first Compensation commensurate with experience#LI-MC1

【公司介紹】這是一家隸屬大型企業集團的知名品牌，長期深耕消費者服務與企業解決方案，近年正全面推動 AI 與數位轉型。公司擁有穩定的市場基礎與龐大的用戶場景，並積極將生成式 AI 導入多元業務流程與產品服務中。目前 AI / Data 團隊由 PM、DA 與 AI Engineer 組成，採用敏捷式開發 (Scrum) 協作模式，並直接獲得高層支持。團隊不僅負責技術研究，更著重於 將 AI 真正落地到產品與商業流程，讓工程師能直接參與從架構設計到應用場景落地的完整過程，對產品與決策產生實際影響。若你期待在穩定資源環境下，挑戰真實商業場景中的 AI 應用，這會是一個能發揮技術價值與影響力的機會。 【工作內容】• 設計與開發 LLM 驅動的 AI Agent 系統架構與核心模組• 建立任務規劃、記憶管理、工具調用與流程執行等 Agent 能力• 利用 Google ADK / Vertex AI 等平台打造具備推理能力的 AI 系統• 建構並優化 RAG（Retrieval-Augmented Generation）架構，降低模型幻覺並提升知識準確度• 整合 Function Calling、Skills 等技術，建立具上下文理解與知識注入能力的智慧系統• 建立 LLM / Agent 評估機制與自動化測試工具，持續提升系統品質與可靠度• 推動 AI 在搜尋、客服、自動化分析與數據流程等場景的應用落地 【使用技術】• Python• SQL / Database Design• RESTful API• LLM Application Development• RAG Architecture• AI Agent Systems• Prompt Engineering 加分技術：• GCP（Vertex AI / Google ADK）• Vector Database（Pinecone / Weaviate / Vertex AI Vector Search）• LLM Evaluation Framework（RAGAS / DeepEval / LangSmith）

介紹 GNTC 團隊 Dcard GNTC 團隊致力於打造企業級 AI 工作平台，讓企業都能透過 AI 提升工作效率、創造更高價值。我們相信 AI 不只是工具，更是每個團隊成員的智能助手，能夠深度整合企業資料與流程，協助團隊做出更精準的決策、產出更高品質的成果。我們提供全方位的企業 AI 工作平台，使企業夥伴可以提升決策與洞察 、加速企劃產出 ，並且能透過 Agent 自動化處理例行任務，讓團隊專注於更具創造性與決策價值的工作。為了達成這個目標，我們需要 Senior Backend Engineer 加入我們，負責 Dcard GNTC 企業 Agent 平台的後端架構設計、AI 模型整合與系統開發。你將專注於打造穩定、可擴展的生成式 AI 後端服務，為企業客戶提供強大的技術支撐。 你將在團隊參與⋯ 設計與開發 Dcard GNTC Agent 平台的後端系統設計並實作 MCP Server、API、AI Workflow整合 LLM、Vector Database、RAG 等 AI 技術優化系統效能、可靠性與可擴展性根據產品規劃與客戶需求，設計並實作技術方案參與技術方案討論，根據時程、成本、技術可行性提出建議將產品需求轉化為清晰的技術架構與實作持續改善平台架構與開發體驗全面瞭解整體系統架構，識別並優化架構建立可復用的技術元件與最佳實踐改善 CI/CD、監控、部署流程技術研究與知識分享持續學習 Agent 相關知識與新技術，評估並導入適合的技術在團隊內部進行技術分享與文件撰寫

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We're seeking a Senior Site Reliability Engineer to join the team. You will build and operate the infrastructure and tooling behind WorldQuant's data ingestion pipelines — systems that onboard, validate, and deliver large-scale datasets to the firm's research platform.This is a 70% build / 30% operate role. You'll spend most of your time engineering automation, observability, and developer tooling, while also participating in on-call rotations and incident response for production data pipelines. You'll partner with engineering, analyst, and research teams to ensure reliability at scale — this requires excellent analytical skills, clear communication, and the ability to collaborate across teams. What You'll Do: Build (70%): Design and develop automation, monitoring, CI/CD, and reliability features for the data onboarding pipeline Develop and maintain internal infrastructure and services that reduce toil and improve pipeline reliability Build observability solutions — dashboards, alerting, log aggregation — using Grafana, the ELK stack, and Vector Design and implement CI/CD pipelines, test automation, and release management workflowsWrite infrastructure-as-code for provisioning, scaling, and managing platform components: Kubernetes, bare metal hosts Integrate and extend tools such as Redis, Celery, MySQL Operate (30%): Keep production data pipelines healthy and respond to incidents Participate in on-call rotation, respond to production incidents, and drive post-mortems Define and track SLOs/SLIs for pipeline reliability, latency, and data freshness Diagnose platform performance and reliability issues, driving them to root cause Create and maintain runbooks for common operational scenarios Plan capacity and optimize resource utilization What You'll Bring 8+ years of experience in SRE, DevOps, or platform engineering roles Linux expertise: Power user proficiency in Linux with ability to manage infrastructure, deploy services, and troubleshoot production systems Python proficiency: Strong scripting and automation skills; experience building CLI tools, API clients, monitoring integrations, and operational tooling in Python Kubernetes containers: Deep hands-on experience with Kubernetes — deploying, scaling, debugging, and managing production workloads. Familiarity with Helm, resource management. Solid experience with Docker Observability: Hands-on experience with monitoring stacks — Grafana, Prometheus, ELK (Elasticsearch, Logstash, Kibana), or similar. Experience designing dashboards, alerts, and SLO-based reliability tracking CI/CD infrastructure-as-code: Experience designing and maintaining CI/CD pipelines (GitLab CI, or similar), including test automation and release management. Familiarity with Ansible or similar IaC tools Databases: Working knowledge of relational databases (MySQL/PostgreSQL), query tuning, and operational database management Message queues streaming: Experience with Kafka, Redis pub/sub, or Celery for event-driven architectures Networking APIs: Understanding of network fundamentals, DNS, load balancing, and REST/gRPC APIs Incident management: Experience with on-call rotations, incident response, post-mortems, and runbook-driven operations Leadership management: Proven track record of leading a team — mentoring engineers, driving technical roadmaps, coordinating cross-team initiatives, and managing priorities. Comfortable owning team delivery and representing the team to stakeholders AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development and operations workflow — treating AI as a force multiplier for automation, incident analysis, and toil reduction Nice to Have: Cloud platforms: Exposure to GCP or AWS for compute, storage, and managed services Data tools: Familiarity with Apache Arrow, gRPC, or columnar data formats Big data platforms: Familiarity with Hadoop or Apache Spark for large-scale data processing Programming languages: C/C++, Golang, Scala, JavaScript Financial services or data-intensive industry background SRE culture: Familiarity with Google's SRE book principles — error budgets, toil tracking, blameless post-mortems What We Offer: Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday We offer a strong culture of learning and development: training courses, library, speakers, share and learn events Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people Premium Health Insurance and Employee Assistance Program Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc. Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams Happy-hour with tea break, snacks and meals every day in the office! #LI-QM1 By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.