Senior AI / ML Cloud Engineer – Graph Analytics Platform
Location:
Company:
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.
explainable AI (XAI)
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.
Entity Resolution
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 asGraphSAGE 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.
