Job Overview
We are seeking a highly skilled AWS Software / Data Engineer to build scalable, production-grade capabilities supporting student intelligence, predictive risk, personalization, knowledge retrieval, and AI context services.
The ideal candidate will have strong hands-on experience across Python, AWS, Terraform, data engineering, software development, and AI/ML services. This role focuses on building reliable, reusable production capabilities rather than being limited to data pipelines, notebooks, or experimentation.
Key Responsibilities
Python Engineering
Develop robust Python applications, APIs, data processing pipelines, automation, and production services.
Build testing frameworks and integrate machine learning and AI capabilities into production applications.
Develop scalable and maintainable software components.
AWS & Infrastructure as Code
Design, implement, and maintain AWS cloud environments using Terraform.
Work with AWS IAM, networking, security, and CI/CD pipelines.
Implement repeatable, governed, and version-controlled infrastructure.
Make safe and reliable infrastructure changes in production environments.
Data Modeling & Context Engineering
Design and implement data solutions using DynamoDB, Aurora, Redshift, Neptune, and S3.
Build longitudinal user profiles and reconcile current and historical states.
Develop behavioral profiles, context attributes, and memory-oriented data solutions.
Applied ML & Predictive Systems
Productionize predictive risk models and reusable ML features.
Implement model scoring, explainability, monitoring, and operational workflows.
Work with Amazon SageMaker, Amazon Bedrock, Feature Store, and Model Monitor.
Retrieval, RAG & Knowledge Systems
Build grounded knowledge retrieval capabilities for AI applications.
Work with Amazon Bedrock Knowledge Bases, OpenSearch, S3, and Lambda.
Support traceable and reliable source retrieval for AI experiences.
Real-Time Data & Integration
Process behavioral and institutional events in near real time.
Build event-driven architectures using:
MSK / Kafka
Kinesis
EventBridge
Lambda
API Gateway
AWS Glue
Production AI & Agent Engineering
Develop production AI and agent-enabled applications using Amazon Bedrock.
Implement secure tool calling, controlled access, observability, and governance.
Work with Bedrock Agents/Runtime, Lambda, ECS/EKS, CloudWatch, IAM, and Secrets Manager.
Required Qualifications
Strong professional experience developing production applications with Python.
Extensive hands-on experience with AWS.
Strong experience with Terraform / Infrastructure as Code.
Experience designing and implementing AWS event-driven and data architectures.
Experience with cloud security, IAM, networking, and CI/CD.
Strong understanding of data modeling and distributed data systems.
Experience building highly available, scalable, production-grade services.
Ability to work across software engineering, data engineering, cloud infrastructure, and AI/ML.
Preferred Qualifications
Experience with Amazon SageMaker and Amazon Bedrock.
Experience building RAG / Retrieval-Augmented Generation solutions.
Experience with Bedrock Knowledge Bases or Bedrock Agents.
Experience with Kafka/MSK, Kinesis, EventBridge, Lambda, and API Gateway.
Experience with DynamoDB, Aurora, Redshift, Neptune, OpenSearch, and S3.
Experience implementing ML model monitoring, feature engineering, and predictive systems.
Experience developing AI/ML-enabled production applications.
Experience with containerized workloads using ECS or EKS.
Strong understanding of observability, security, secrets management, and production governance.
What We're Looking For
The ideal candidate is a full-lifecycle engineer who can take a solution from:
Data & Events User Profiles / Features Predictive or AI Context Production Service
Candidates who can operate effectively across data, software, infrastructure, and AI/ML will be particularly well suited for this opportunity.
