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Python Kubernetes Software Engineer Data Jobs in Henrico, VA

Estes Express

Software Engineer III

Richmond, VA · On-site

$90 - $157/hr

They will share their passion for marrying data with emerging technologies to create modern ... and Python, SQL and NoSQL databases, and Container Orchestration services like Kubernetes

New

Ampcus Inc

Lead / Software Engineer

Richmond, VA · On-site

... for data analysis and AI/ML applications. • Automating processes using Python scripts and ... Kubernetes (which is itself written in Go). • Integrating with various databases (PostgreSQL ...

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AI/ML Engineer + Data engineer (W2)

Snowrelic Inc

Glen Allen, VA • Remote

$117K - $140K/yr

Contractor

Re-posted 16 days ago

Job description

AI/L Engineer

remote (USA)

contract to hire, . 

  

Top skills: 

Python; Java nice to have 

AWS Cloud 

AI/ML; A/B framework 

Data Engineering 

Containerization 

DevOps 

  

looking for an Engineer with a strong background in data engineering, cloud infrastructure, and AI/ML application development. This 6-month contract role (with potential for hire) offers the opportunity to work on cutting-edge Generative AI and Large Language Model (LLM) solutions that power digital transformation. 

  

In this position, you’ll lead the design, development, and deployment of secure, scalable AI applications on AWS, driving modernization across critical business platforms. The ideal candidate will be passionate about AI innovation, cloud technologies, and collaborative engineering, with proven skills in SQL, software design principles, and Agile delivery. 

  

You’ll work within a high-performing Agile team focused on advancing our enterprise’s next-generation capabilities—building reliable, ethical, and high-quality solutions that directly support our strategic growth goals. 

  

Key Responsibilities 

  • Lead the end-to-end development and deployment of AI/ML and cloud-based applications, from concept through production. 

  • Design and maintain secure AWS infrastructure, focusing on scalability, performance, and compliance. 

  • Implement AI/ML best practices, including prompt engineering, data versioning, systematic experimentation, and A/B testing. 

  • Develop, test, and integrate high-performance applications, APIs, and data solutions supporting  products and modernization goals. 

  • Write clean, testable, and maintainable code, following SOLID principles and software engineering best practices. 

  • Create and maintain clear, detailed technical documentation for all systems and processes. 

  • Collaborate effectively within Agile teams using tools such as Jira and Confluence, contributing to sprint planning, reviews, and retrospectives. 

  • Participate in on-call rotations to provide timely technical support for production systems. 

  • Communicate proactively, identifying and escalating risks or blockers early. 

  • Promote a culture of inclusion, continuous learning, and technical excellence. 

  

Technical Skills 

  • Python, Java, C#, JavaScript/TypeScript 

  • SQL, DB2, SQL Server, PostgreSQL, NoSQL (MongoDB or DynamoDB) 

  • AWS (CloudFront, EC2, Lambda, S3, RDS); Azure experience a plus 

  • LLMs, model deployment, prompt engineering, data pipelines, A/B testing frameworks 

  • Git, Docker, Kubernetes, Terraform, Jenkins, API Gateway, RESTful API development 

  • ETL pipelines, data versioning, and performance optimization 

  • Unit and integration testing, automated CI/CD pipelines, test coverage tools 

  • Solid understanding of Agile and SAFe practices.  

  

Qualifications 

  • Bachelor’s degree in computer science, Engineering, or a related field (master’s preferred). 

  • Minimum 7 years of experience in software engineering, data management, or cloud application development. 

  • Proven experience leading complex development efforts involving AI/ML or cloud technologies. 

  • Strong analytical and problem-solving skills, with the ability to work autonomously and adapt to evolving project needs. 

  • Excellent verbal and written communication skills, with the ability to collaborate across technical and non-technical teams. 

  • Demonstrated commitment to quality, security, and continuous improvement.