Sr. Full Stack Ai Engineer

Senior Full Stack Engineer – Enterprise Analytics Platform Location: Remote (Preference for India-based candidates)Compensation: Competitive salary + significant equity package Company: Contex Q (Singapore HQ)About Contex QAt Contex Q, a Singapore based B2 B Saa S AI Start-up, we're redefining how organizations tackle some of the world's toughest challenges—financial crime, fraud, and risk management—through a groundbreaking contextual decision intelligence platform.

By marrying symbolic AI, vector, and graph AI, we process trillions of data points from corporate registries, ESG, SDG, and supply chain data to deliver transparent, ethical, and actionable insights.

Our mission is to empower organizations with unparalleled intelligence while upholding the highest standards of integrity and societal impact.

Join us to build a Next Gen Contextual Decision Intelligence Enterprise Analytics Platform that will set a new standard for **explainable AI (XAI) **in high-stakes industries.

The Opportunity We're seeking a passionate and sharp Full Stack Developer to architect and build the front-end and back-end systems for Contex Q'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.

This is a chance 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.

Role Overview We are looking for a **Senior Full Stack Engineer ** to drive the development of user-facing solutions built on our custom graph database and high-performance analytics engine.

You will work with advanced backend technologies—Hadoop, Apache Spark, and Scala—to deliver high-impact data applications, real-time dashboards, and intuitive interfaces that make complex analytics accessible to business users.

This role requires building systems that handle visualization of graphs with millions of nodes, deliver sub-100ms API response times at scale, and process TB-scale datasets in real-time.

Core Responsibilities Frontend & Visualization (40%)Build responsive, scalable web apps (React/Type Script) for advanced enterprise analytics and data visualization Develop interactive graph/network visualizations capable of rendering millions of nodes and edges smoothly Optimize frontend performance for real-time exploration of large, multi-dimensional datasets Design interfaces for explainable AI and complex entity relationship analytics Implement advanced rendering techniques (Web GL, canvas virtualization) for massive dataset visualization Backend & API Development (35%)Architect and implement fast, scalable Graph QL/REST APIs with sub-sec response times for analytics, entity resolution, and graph queries Develop and orchestrate microservices using Node.js, Python, Scala Build and maintain data transformation and aggregation pipelines, optimizing for low-latency and high throughput Integrate backend analytics powered by Apache Hadoop, Spark, and our proprietary graph database Work with our custom graph query language and SDKs to expose graph analytics capabilities Cloud Infrastructure & Data Platform (25%)Deploy, scale, and monitor services on GCP (Kubernetes, GKE, Cloud Run, Pub/Sub)Implement cloud functions and serverless analytics workflows Design and optimize large-scale data processing pipelines handling TB-scale data with Apache Hadoop and Spark Collaborate with data engineers on ETL processes, data architecture, and real-time data integration strategies Ensure platform reliability with 99.9% uptime SLAs Required Qualifications Technical Skills Atleast 5–8+ years' experience as a full stack engineer in analytics, big data, or enterprise environments Strong hands-on experience with React, Type Script, D3.js, Web GL, Node.js, Python, Scala Advanced expertise with Hadoop and Apache Spark for distributed data processing and analytics Experience building rich data visualizations and enterprise dashboards handling millions of data points Proficient in** API design** (Graph QL/REST), microservices, and optimizing for real-time and large-scale data flows Database exposure: Postgre SQL, Redis, Elasticsearch; experience designing or scaling custom graph engines a plus**GCP experience **with services like GKE, Pub/Sub, Big Query, and Cloud Run Dev Ops & Deployment Enable Scalable Deployment: Deploy and manage services on cloud platforms (AWS/Azure/GCP) using Docker and Kubernetes, optimizing for low-latency (

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