What are the responsibilities and job description for the Python AWS Engineer (AI/ML) (On Site) position at BURGEON IT SERVICES LLC?
Python AWS Engineer (AI/ML)
Location: Wilmington, DE (Onsite)
Experience: 10 12 Years
Duration: Long Term
Job Summary
We are looking for a highly skilled Python AWS Engineer with strong expertise in cloud-native application development, distributed data processing, and DevOps practices. The ideal candidate should have hands-on experience in Python development, AWS cloud services, infrastructure automation, and scalable data engineering solutions. Exposure to AI/ML technologies and AI-assisted development tools is highly preferred.
Required Skills
- Python
- AWS
- Terraform
- AI/ML
Key Responsibilities
- Design, develop, and maintain scalable and high-performance Python applications.
- Build and optimize distributed data processing solutions using PySpark and Spark SQL.
- Develop and manage ETL/data pipelines and orchestration workflows using tools such as Airflow, Kafka, Jenkins, and Spinnaker.
- Implement infrastructure automation and provisioning using Terraform.
- Work extensively with AWS cloud services including:
- S3
- EC2
- Lambda
- ECS
- EventBridge
- Develop REST APIs and backend services using frameworks such as Flask or Django.
- Perform unit testing, integration testing, debugging, and troubleshooting using frameworks like PyTest and PyUnit.
- Collaborate with cross-functional teams to deliver scalable and reliable solutions.
- Implement CI/CD pipelines and DevOps best practices for automated deployments.
- Participate in architecture discussions and performance optimization initiatives.
- Explore and integrate AI/ML capabilities into enterprise applications where applicable.
Required Qualifications
- Strong proficiency in Python programming with excellent coding and problem-solving skills.
- Hands-on experience with PySpark, Spark APIs, and distributed data processing.
- Strong knowledge of Python libraries/frameworks including:
- Pandas
- NumPy
- Flask
- Django
- Strong understanding of scalable system design and cloud-native architectures.
- Experience working with AWS cloud services and infrastructure.
- Experience with CI/CD pipelines and DevOps methodologies.
- Hands-on experience with Infrastructure-as-Code tools such as Terraform.
- Strong debugging, testing, and troubleshooting skills.
Preferred Qualifications
- Experience with Snowflake or Databricks.
- Exposure to Machine Learning and Artificial Intelligence frameworks/tools.
- Familiarity with AI-assisted development tools such as GitHub Copilot.
- Understanding of Large Language Models (LLMs) and AI-driven productivity solutions.
Soft Skills
- Strong communication and collaboration skills.
- Ability to work effectively in a fast-paced Agile environment.
- Strong analytical and troubleshooting abilities.
- Self-motivated and detail-oriented mindset.