AI Data Engineer

About the role

As an AI Data Engineer, you will make an impact by designing, building, and optimizing scalable cloud-native data engineering solutions that enable advanced AI-driven applications and business outcomes. You will be a valued member of our engineering team and collaborate closely with data engineers, software engineers, architects, product owners, and business stakeholders to deliver innovative solutions across the AWS ecosystem.

In this role, you will:

• Design, develop, and support scalable data pipelines, data integrations, and processing solutions using modern cloud-native technologies.
• Build production-grade Python applications, scripts, and AWS Lambda functions that integrate with enterprise platforms, APIs, and AWS services.
• Develop and enhance data platforms leveraging technologies such as AWS Glue, AWS DMS, Apache Kafka, Apache Airflow, and Snowflake.
• Translate business and technical requirements into engineering specifications, technical designs, and measurable acceptance criteria.
• Review, validate, test, debug, and optimize AI-generated code while applying engineering best practices throughout the software development lifecycle.

Work model

We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a remote position open to qualified applicants. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• Strong hands-on Python development experience with demonstrated success delivering production-quality code.
• Proven data engineering experience building, deploying, and supporting scalable data pipelines and processing solutions.
• Hands-on expertise with AWS services and cloud-native data engineering architectures.
• Experience working with one or more of the following technologies: AWS Glue, AWS DMS, Apache Kafka, Apache Airflow, or Snowflake.
• Experience using AI-assisted development tools such as Claude Code, Kiro, or similar technologies to accelerate software engineering while maintaining engineering rigor.
• Ability to convert business requirements into technical specifications, solution designs, and acceptance criteria.
• Experience reviewing, testing, debugging, and optimizing AI-generated code before production deployment.
• Hands-on experience developing AWS Lambda functions using Python and integrating them with AWS services.

These will help you stand out

• Experience with Kiro, including specification-driven development approaches.
• Practical experience using Claude Code for software engineering or data engineering initiatives.
• Knowledge of Model Context Protocol (MCP) and MCP-based integrations.
• Experience implementing automated testing frameworks, CI/CD pipelines, deployment automation, and code-quality controls.
• AWS certifications such as AWS Certified Data Engineer, AWS Certified Developer, or AWS Certified Solutions Architect.
• Working knowledge of Type Script.
• Understanding of agentic AI engineering concepts, including agents, tools, memory, workflow orchestration, and human-in-the-loop patterns.

Preferred differentiators

Candidates will stand out if they have experience with:

• Agent development frameworks such as Strands Agents SDK or similar agentic AI platforms.
• Designing and implementing MCP servers, tools, and integrations.
• Creating reusable engineering standards, development patterns, specifications, and governance practices for AI-assisted development.
• Building agentic workflows and…