Senior Software Engineer Consultant (Python/Django)

• Bachelor s degree in Computer Science Engineering Data Science or equivalent hands-on experience.
• 5 years software development experience including:
  • Python and Django (or similar frameworks) REST APIs Angular/React (or similar).
  • SQL and object-relational mapping; designing and tuning relational databases.
  • AWS cloud services: EC2 S3 Lambda RDS ElasticSearch SQS/SNS.
  • Git CI/CD pipelines (Jenkins CodePipeline) containerization (Docker) and orchestration (Kubernetes).
• 1-2 years experience integrating or deploying machine learning models in production.

Role Overview

The Senior Software Engineer will be focused on extending the Python/Django REST microservices platform for a modern high profile system. In addition to core development the ideal candidate will integrate deploy and maintain machine-learning models (e.g. recommendation engines predictive analytics NLP interfaces) in AWS.

Key Technical Areas

• Core Stack: Python 3.x Django REST Framework SQL/RDS Angular or React front-ends
• Cloud & DevOps: AWS (EC2 S3 Lambda RDS ElasticSearch SQS/SNS SageMaker) Docker/Kubernetes Jenkins or CodePipeline
• AI/ML Integration: Collaborate with data scientists to productionize TensorFlow/PyTorch models build MLOps pipelines (MLflow Kubeflow) implement CI/CD for model retraining and monitoring
• Data & Compliance: Design data schemas and pipelines for training/inference ensure FERPA-compliant data governance and privacy

Job Description:

USEReady seeks an experienced senior software engineer to join the development team (onshore and offshore) building a modern critical system. You will help deliver new functionality migrate legacy data and integrate services all while embedding AI/ML-powered features (predictive analytics recommendation engines and NLP interfaces) into the Python/Django REST microservices architecture on AWS.

Work hands-on writing code designing data schemas and deploying both traditional and ML components. Partner closely with data scientists infrastructure security and project management to ensure robust scalable and secure services that improve student and administrator experiences.

KEY RESPONSIBILITIES

• Development & Architecture
  • Implement and maintain Python/Django REST services and Angular/React front-ends.
  • Design and optimize SQL database schemas; build data pipelines for ML training and inference.
  • Integrate machine learning models (e.g. TensorFlow PyTorch) into microservices for features like course recommendations retention risk scoring and automated data validation.
• Cloud & DevOps
  • Build and manage AWS infrastructure: EC2 S3 Lambda RDS ElasticSearch SQS/SNS SageMaker (or equivalent).
  • Extend CI/CD pipelines (Jenkins AWS CodePipeline Docker/Kubernetes) to support automated model retraining testing and deployment.
  • Monitor system and model performance; implement logging alerting and cost-optimization best practices.
• Collaboration & Mentorship
  • Partner with Data Science to translate business use-cases into ML workflows (data ingestion feature engineering model tuning).
  • Review peers code and mentor junior developers on Python Django AWS services and MLOps practices.
  • Communicate complex technical and AI/ML concepts clearly to both technical and non-technical stakeholders.
• Standards & Compliance
  • Enforce coding security and data-privacy standards (FERPA compliance) across development and deployment.
  • Maintain documentation for codebases ML pipelines and operational runbooks.
  • Participate in sprint planning estimation and technical road-mapping.

REQUIRED EXPERIENCE:

• Bachelor s degree in Computer Science Engineering Data Science or equivalent hands-on experience.
• 5 years software development experience including:
  • Python and Django (or similar frameworks) REST APIs Angular/React (or similar).
  • SQL and object-relational mapping; designing and tuning relational databases.
  • AWS cloud services: EC2 S3 Lambda RDS ElasticSearch SQS/SNS.
  • Git CI/CD pipelines (Jenkins CodePipeline) containerization (Docker) and orchestration (Kubernetes).
• 1 2 years experience integrating or deploying machine learning models in production.
• Strong analytical problem-solving and debugging skills.
• Excellent communication teamwork and ability to manage shifting priorities.

DESIRED EXPERIENCE:

• Master s degree or higher in a technical field (Data Science AI/ML Computer Science).
• Prior work on Higher Education or Student Information Systems.
• Hands-on experience with MLOps frameworks (MLflow Kubeflow) and cloud ML services (SageMaker Vertex AI).
• Familiarity with NLP libraries (spaCy Hugging Face Transformers) for chatbots or text analytics.
• Experience with data governance privacy regulations and ethical AI practices in educational contexts.