Senior AI and Software Engineer
Own the Architecture. Build the Intelligence. Scale the Network. uParcel operates one of Singapore’s largest last-mile delivery networks, and we are evolving our platform into a fully autonomous, AI-driven logistics engine. We’re hiring a Senior AI & Software Engineer to architect and build the core intelligence that powers real-time job assignment, routing efficiency, and driver-matching logic at scale. This is a high-impact engineering role for someone who wants to design distributed systems, build production-grade ML pipelines, and shape the technical direction of a fast-growing logistics platform.
Core Responsibilities
System Architecture & Backend Engineering Architect and implement backend services using Python, Django, and modernmicroservice patterns Design scalable, fault-tolerant systems deployed on AWS (EC2, ECS/Lambda,RDS, S3, CloudWatch, API Gateway, IAM, containers) Build high-performance APIs for real-time decisioning, driver-job matching, andoperational workflows Implement asynchronous processing pipelines using Celery, SQS, or equivalent AI/ML Engineering
Lead the design and development of uParcel’s AI-driven job assignment engine,incorporating: Real-time geospatial data Driver availability, historical performance, and behavioral patterns Delivery SLAs, urgency, and route constraints Predictive ETA and load balancing models Build ML pipelines for training, evaluation, and deployment (batch + real-timeinference) Implement model monitoring, drift detection, and continuous retrainingworkflows Data Engineering & Infrastructure
Design data schemas and pipelines to support high-volume event ingestion Work with geospatial datasets, map APIs, and routing algorithms Optimize query performance on relational and NoSQL datastores Ensure observability across services (metrics, tracing, structured logs) Technical Leadership
Drive architectural decisions and enforce engineering best practices Conduct deep technical code reviews and mentor mid-level engineers Collaborate with product, operations, and data teams to translate business logicinto deterministic, scalable systems Own end-to-end delivery of features from design to production rollout Required Technical Expertise
Strong computer science fundamentals: algorithms, data structures, distributedsystems Expert-level proficiency in Python and production experience with Django Deep understanding of AWS cloud architecture and infrastructure design Experience building and deploying ML models in production environments Strong knowledge of RESTful API design, microservices, and asynchronoussystems Familiarity with geospatial computation, routing algorithms, or optimizationmodels Experience with CI/CD pipelines, containerization (Docker), and IaC(CloudFormation) Ability to reason about system performance, scalability, and reliability Bonus Skills
Experience with reinforcement learning or real-time decision engines Background in logistics, fleet optimization, or marketplace matching systems Knowledge of graph algorithms, heuristics, or constraint-solving techniques
System Architecture & Backend Engineering Architect and implement backend services using Python, Django, and modernmicroservice patterns Design scalable, fault-tolerant systems deployed on AWS (EC2, ECS/Lambda,RDS, S3, CloudWatch, API Gateway, IAM, containers) Build high-performance APIs for real-time decisioning, driver-job matching, andoperational workflows Implement asynchronous processing pipelines using Celery, SQS, or equivalent AI/ML Engineering
Lead the design and development of uParcel’s AI-driven job assignment engine,incorporating: Real-time geospatial data Driver availability, historical performance, and behavioral patterns Delivery SLAs, urgency, and route constraints Predictive ETA and load balancing models Build ML pipelines for training, evaluation, and deployment (batch + real-timeinference) Implement model monitoring, drift detection, and continuous retrainingworkflows Data Engineering & Infrastructure
Design data schemas and pipelines to support high-volume event ingestion Work with geospatial datasets, map APIs, and routing algorithms Optimize query performance on relational and NoSQL datastores Ensure observability across services (metrics, tracing, structured logs) Technical Leadership
Drive architectural decisions and enforce engineering best practices Conduct deep technical code reviews and mentor mid-level engineers Collaborate with product, operations, and data teams to translate business logicinto deterministic, scalable systems Own end-to-end delivery of features from design to production rollout Required Technical Expertise
Strong computer science fundamentals: algorithms, data structures, distributedsystems Expert-level proficiency in Python and production experience with Django Deep understanding of AWS cloud architecture and infrastructure design Experience building and deploying ML models in production environments Strong knowledge of RESTful API design, microservices, and asynchronoussystems Familiarity with geospatial computation, routing algorithms, or optimizationmodels Experience with CI/CD pipelines, containerization (Docker), and IaC(CloudFormation) Ability to reason about system performance, scalability, and reliability Bonus Skills
Experience with reinforcement learning or real-time decision engines Background in logistics, fleet optimization, or marketplace matching systems Knowledge of graph algorithms, heuristics, or constraint-solving techniques