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 : ContexQ (Singapore HQ)

About ContexQ

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.

The Opportunity

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.

Role Overview

We are looking for a

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 / 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%)

Architect and implement fast, scalable GraphQL / 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, 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

Database exposure : PostgreSQL, Redis, Elasticsearch ; experience designing or scaling custom graph engines a plus

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.

Tech Stack You'll Work With (Not Exhaustively listed here due to working on Stealth Mode)

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

Startup or high-growth environment exposure

General Qualifications :

PhD or Master's (Preferred) degree in Computer Science, Software Engineering, or a related field. Experience with agile development methodologies.

Excellent communication skills for explaining complex technical ideas. Solid understanding of software engineering best practices and design patterns.

Mindset

Proactive, self-driven, and comfortable tackling ambiguous and complex technical problems

Adaptable and eager to take on multiple roles in a dynamic, product-focused team

Deep passion for building transformative, high-performance analytics technology

Quick learner ready to master our proprietary systems while leveraging core distributed systems expertise

What You'll 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

Our Technology

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)

SDKs and APIs : Well-documented interfaces for all platform capabilities

Scale : Handle billions of entities, TB-scale processing, and millisecond query responses

Why Join Us

Impact : Shape the architecture of an essential platform for enterprise decision-making

Innovation : Work on proprietary graph technology, big data pipelines, and cutting-edge AI

Growth : Influence core engineering and play a central role in building the early team

Learning : 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

Modern Stack

React, TypeScript, D3.js, Deck.gl, Node.js, Python, Scala, Hadoop, Spark, PostgreSQL, Redis, BigQuery, GCP, Docker, Kubernetes, Custom Graph Engine

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 Fit Discussion with Founders

Join us in building the next generation of enterprise analytics. We provide comprehensive onboarding for our proprietary systems but expect quick ramp-up on core distributed systems concepts. 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.