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
At ContexQ, a Singapore based B2B SaaS 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 NextGen Contextual Decision Intelligence Enterprise Analytics Platform that will set a new standard for **explainable AI (XAI) **in high-stakes industries.
We’re seeking a passionate and sharp Full Stack Developer to architect and build the front-end and back-end systems for 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.
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.
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.
Frontend & Visualization (40%)
Build responsive, scalable web apps (React/TypeScript) 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 (WebGL, canvas virtualization) for massive dataset visualization
Backend & API Development (35%)
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
Atleast 5–8+ years' experience as a full stack engineer in analytics, big data, or enterprise environments
~ Strong hands-on experience with React, TypeScript, D3.js, WebGL, 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** (GraphQL/REST), microservices, and optimizing for real-time and large-scale data flows
~ Database exposure: PostgreSQL, Redis, Elasticsearch ; experience designing or scaling custom graph engines a plus
~**GCP experience **with services like GKE , Pub/Sub, BigQuery, and Cloud Run

DevOps & Deployment
Enable Scalable Deployment: Deploy and manage services on cloud platforms (AWS/Azure/GCP) using Docker and Kubernetes, optimizing for low-latency () Ethical & Explainable AI Focus Champion Transparency:
Integrate principles of fairness and interpretability into API design and frontend visualizations, ensuring outputs align with XAI goals and are understandable to users.
Backend & Processing: Python (FastAPI), Scala (optional exploration for specific tasks), Apache Spark, Hadoop, Iceberg, Elasticsearch Databases: PostgreSQL, Milvus (Vector DB), MongoDB (NoSQL) Frontend: React, Tailwind CSS, D3.js, Plotly DevOps: Docker, Kubernetes, AWS/Azure/GCP, CI/CD tools (e.g., Jenkins, GitLab CI) AI Integration: Familiarity with integrating outputs from libraries like NetworkX, PyG (for GNNs), SHAP, LIME (for XAI).
Preferred Experience
Deploying and optimizing big data analytics pipelines in Hadoop/Spark ecosystems
Using Scala for high-performance backend systems, data transformations, or distributed applications
Hands-on work with enterprise analytics, operational intelligence, or business reporting platforms
Experience with graph-based data modeling, entity resolution, or custom database architectures
Working with proprietary query languages or custom database SDKs
PhD or Master's (Preferred) degree in Computer Science, Software Engineering, or a related field. Experience with agile development methodologies.
Solid understanding of software engineering best practices and design patterns.
Deep passion for building transformative, high-performance analytics technology
Visual interactive exploration of enterprise networks with millions of entities
Analytics Dashboards : Real-time operational, risk, and business metric monitoring processing TB of data
Visualize supply chain, ESG, and other key KPIs with sub-second response
Navigate and analyze hidden relationships in enterprise data using our proprietary graph engine
Proprietary Graph Database : Custom-built for multi-dimensional analytics, offering 10x performance over traditional graph DBs
Custom Query Language : Purpose-built for complex enterprise analytics (comprehensive training provided)
Innovation : Work on proprietary graph technology, big data pipelines, and cutting-edge AI
Influence core engineering and play a central role in building the early team
Comprehensive onboarding on our proprietary systems with continuous learning opportunities
Flexibility & Equity : Significant early-stage equity, learning resources, and a high-impact remote-first culture
React, TypeScript, D3.js, Deck.gl, Node.js, Python, Scala, Hadoop, Spark, PostgreSQL, Redis, BigQuery, GCP, Docker, Kubernetes, Custom Graph Engine
Includes full-stack, big data, and cloud architecture
# Build a complex data visualization or analytics component
# Join us in building the next generation of enterprise analytics. If you're excited about pushing the boundaries of what's possible with data visualization and analytics at scale, we want to hear from you.

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