Senior AI and Software Engineer
Summary
Architect and build an AI-driven logistics engine for a last-mile delivery network, designing distributed systems, ML pipelines, and real-time routing logic in Python on AWS.
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