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

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