Senior AI / ML Cloud Engineer – Graph Analytics Platform Location: Remote Company: ContexQ Pte Ltd About ContexQ ContexQ, a Singapore-based B2B SaaS AI startup, is dedicated to transforming financial crime, fraud, and risk management through a groundbreaking contextual decision intelligence platform. It processes billions of data points from various sources using Symbolic AI, Vector Search, Graph AI, and Agentic frameworks to deliver transparent, ethical, and actionable insights to clients. Our mission is to empower organizations with unparalleled intelligence while maintaining the highest standards of integrity and societal impact. This is an opportunity to solve intricate technical challenges, from real-time very large data processing to advanced analytics and optimisation on very large network graphs and interactive graph visualizations, while contributing to a mission that fights financial crime, builds customer intelligence and promotes ethical decision-making. By joining us, you will help build a NextGen Contextual Decision Intelligence Enterprise Analytics Platform that will set a new standard for explainable AI (XAI) in high-stakes industries. Role Overview and Core Responsibilities The role is a hands-on technical leadership position focused on architecting and implementing distributed graph computing solutions processing billions of entities and relationships for a next-generation data intelligence platform using a microservices architecture. The successful candidate will lead the development of the Entity Resolution and Network Generation services. The engineer is expected to be performance-obsessed, think in distributed systems, optimize for latency and throughput, and act as a self-directed technical leader who makes architectural decisions and implement them. This is a foundational role offering the unique opportunity to design, build, and steer a product from its inception, establishing yourself as a key architect in one of the world's leading Graph analytics platforms. What you will build / contribute to: Entity Resolution Service Design and implement distributed entity resolution algorithms to process billions of records. Build blocking strategies (e.g., LSH, canopy clustering) optimized for Spark at scale. Create AI/ML based advanced matching with explainable AI (XAI). Implement incremental resolution supporting real-time and batch modes. Design APIs for entity lookup with sub-100ms latency requirements. Assist the team in building dynamic entity resolution with embedded graph knowledge of GNN and GT (Graph transformers). Network Generation Service Architect distributed graph generation pipelines using libraries such as GraphX/GraphFrames. Implement graph analytics algorithms such as PageRank, community detection, and centrality measures. Design storage strategies for multi-billion edge graphs in the cloud Build temporal graph support for time-evolving networks. Create high-performance graph serving APIs with complex query capabilities. Optimize graph partitioning to minimize shuffle and maximize locality. AI/ML Model Development & Explainable AI (XAI) Build Graph Neural Networks (GNNs) and models using neighbour sampling techniques such as GraphSAGE to analyse corporate and transaction networks for fraud and risk patterns. Implement AI based Entity Resolution algorithms using techniques such as fuzzy matching, semantic matching (Sentence-BERT), and clustering across heterogeneous data sources. Create Risk Scoring Models by combining rule-based, supervised and unsupervised methods, optimized for real-time and large data processing. Champion model transparency and fairness by integrating state-of-art models evaluation techniques such as SHAP, LIME, bias detection and monitoring model drifts. Cloud Infrastructure & Data Platform (Cross-Service Responsibilities) Ensure seamless integration between entity resolution and network generation services. Implement comprehensive monitoring and observability. Contribute to API design and service contracts. Minimum Qualifications 3+ years of experience in distributed computing and big data systems . 1+ years ’ experience in entity resolution and graph analytics at scale . Strong understanding of blocking algorithms, probabilistic record linkage, and similarity measures. Ability to design and optimise large Apache Spark workloads. Ability to implement graph algorithms in distributed computing frameworks such as Apache Spark, Dask or equivalent with optimised queries and storage formats Have a good understanding of Open Cypher , Gremlin or equivalent. Familiar with Elasticsearch or equivalent for fast search and pattern matching. Understanding of AI/ML applications to entity resolution. Preferred Experience Master or PhD in Computer Science or related field with focus on graphs/entity resolution Experience with Architecture Design and implementation of large scaled Graph databases (Neo4j, Amazon Neptune, JanusGraph) or equivalent Track record in building systems processing millions of entities/edges Experience in designing microservices architectures, fault-tolerant, scalable systems, and API design. Experience with real-time stream processing (Kafka, Flink, Apache Beam, Apache Spark Streaming etc…) Basic experience with Banking compliances (Financial Crime, Fraud) Why Join Us? This is a unique opportunity for the right candidate to solve intricate technical challenges, push the boundaries of what's possible with distributed graph computing and build a platform that fights financial crime with: Impact : You will shape the architecture of an essential platform for enterprise decision-making. Innovation : The role offers the chance to work on advanced network graph technologies, big data pipelines, and cutting-edge AI/ML technologies. Growth : You will influence core engineering and play a central role in building the early team. Learning : ContexQ provides comprehensive onboarding on its ecosystem. It offers continuous learning opportunities and mentorship from senior Data Analytics & AI practitioners. Flexibility & Equity : This is your opportunity to be more than just an employee and become an entrepreneur in the true sense where you have significant upside as our organization grows into the future. Eventually, you will earn great base salary, significant early-stage equity, learning resources, and a high-impact remote-first culture. This includes a Long-term Incentive plan with 75% of base as bonus at the end of the 4th year in service. Join us in building the next generation of Graph analytics! What are we looking for in the candidate? Someone who is motivated by challenge and excited about the opportunity to do build a solution dealing with trillions of data points and the associated complexity. Someone who highly values “integrity” and “merit”. Someone who is unafraid of reaching out to others for help and willing to help, go over and above your immediate role to work collaboratively with others. Application Process Technical Screening: Includes full-stack, big data, and cloud architecture Take-Home Challenge: Build an Entity Resolution module that uses Graph analytics Technical Team Interview Culture-add discussion with ContexQ leadership.
Senior Full Stack Data Engineer Enterprise Analytics Platform Location: Remote (Preference for India-based candidates) Compensation: Competitive salary + significant equity package Company: ContexQ (Singapore HQ) About ContexQ ContexQ, a Singapore-based B2B SaaS AI startup, is dedicated to transforming financial crime, fraud, and risk management through a groundbreaking contextual decision intelligence platform. It processes billions of data points from various sources using Symbolic AI, Vector Search, Graph AI, and Agentic frameworks to deliver transparent, ethical, and actionable insights to clients. Our mission is to empower organizations with unparalleled intelligence while maintaining the highest standards of integrity and societal impact. This is an opportunity to solve intricate technical challenges, from real-time very large data processing to interactive graph visualizations, while contributing to a mission that fights financial crime, builds customer intelligence and promotes ethical decision-making. By joining us, you will help build a NextGen Contextual Decision Intelligence Enterprise Analytics Platform that will set a new standard for explainable AI (XAI) in high-stakes industries. Role Overview and Core Responsibilities We're seeking a passionate and sharp Full Stack Data Engineer to architect and build the front-end and back-end systems for the ContexQ's platform. You'll work closely with our AI Engineers to create a scalable, intuitive platform that visualizes complex network relationships, delivers real-time risk scores, and integrates with advanced AI models. The role involves solving intricate technical challenges, from very large data processing to interactive graph visualizations. This includes: Frontend & Visualization (15%) Build responsive, scalable web applications using React and TypeScript for enterprise analytics and data visualization. Develop interactive graph visualizations that can render millions of nodes and edges smoothly. Optimizing frontend performance for real-time exploration of large, multi-dimensional datasets Designing interfaces for explainable AI. Backend & API Development (35%) Architect and implement fast, scalable GraphQL/REST/gRPC APIs. Develop and orchestrate micro-services using Node.js, Python or an equivalent language. Build and maintain data transformation and aggregation pipelines, optimizing for low latency and high throughput. Integrate with backend analytics powered by the Apache Spark eco-system. Use custom graph query language and SDKs to expose graph analytics capabilities. Cloud Infrastructure & Data Platform (50%) Deploy, scale, and monitor services on GCP using services such as Managed Airflow, Kubernetes with GKE, Cloud Run, etc. Implement cloud functions and serverless analytics workflows. Design and optimize large-scale data processing pipelines handling terabytes of data with Apache Spark. Qualifications General A Master's in Computer Science or a related field is preferred. Excellent communication skills for explaining complex technical ideas to non-technical audience Solid understanding of software engineering best practices and design patterns Minimum Qualifications: At least 4 to 6+ years of experience as a full-stack engineer in analytics, big data, or enterprise environments. Strong hands-on experience with Node.js, Java, Python or equivalent. Proficiency with AWS or GCP services such as EKS / GKE, Kinesis / Kafka / Pub/Sub, BigQuery / RedShift, and Lambda functions / Cloud Run. Proficiency in API design (GraphQL/REST/gRPC) with AI Gateways and containers based micro-services. Experience deploying and managing services on cloud platforms (AWS/Azure/GCP) using Terraform and containerised services with Docker and Kubernetes. Experience with major databases (SQL, NoSQL) and cloud based data warehouses (RedShift. BigQuery, Snowflake) Preferred Experience: Experience with distributed data processing and machine learning frameworks such as Apache Spark and Ray, and proficiency in Scala or PySpark. Hands-on work with enterprise analytics, operational intelligence, or business reporting platforms. Experience with graph-based data modelling, entity resolution, or custom database architectures would be a plus. What you will build Graph Investigation Console : Visual interactive exploration of enterprise networks with millions of entities Entity Resolution Workbench : Approve and audit entity matches with explainable analytics at scale Analytics Dashboards : Real-time operational, risk, and business metric monitoring processing TB of data Advanced Reporting Interfaces : Visualize supply chain, ESG, and other key KPIs with sub-second response Custom Graph Explorer : Navigate and analyze hidden relationships in enterprise data using our proprietary graph engine Why Join Us This is an opportunity to solve intricate technical challenges and build a platform that fights financial crime. Impact : You will shape the architecture of an essential platform for enterprise decision-making.. Innovation : The role offers the chance to work on proprietary graph technology, big data pipelines, and cutting-edge AI technologies. Growth : You'll also have the opportunity to influence core engineering and play a central role in building the early team. Learning : ContexQ provides comprehensive onboarding on its proprietary systems. It offers continuous learning opportunities and mentorship from senior Data Analytics & AI practitioners. Flexibility & Equity : The company offers a competitive compensation, significant early-stage equity, learning resources, and a high-impact remote-first culture. Join us in building the next generation of enterprise analytics! Application Process Technical Screening: Includes full-stack, big data, and cloud architecture Take-Home Challenge: Build a complex data visualization or analytics component Technical Team Interview Culture add Discussion with Founders