Build cloud-native and serverless applications using AWS services, including Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, Sage Maker, and related tools. Strong hands-on experience with AWS-native services, including Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, and SageMaker, is required.
Numbers & Facts
Location
Detroit, MI
Description
Our Client, a Health Insurance company, is looking for a Data Science Senior Analyst/AI Engineer for their Detroit, MI/ Hybrid location.
Responsibilities:
Design, develop, test, and deploy end-to-end backend solutions that support AI, machine learning, and intelligent automation use cases.
Build cloud-native and serverless applications using AWS services, including Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, Sage Maker, and related tools.
Develop APIs, workflow automation, and integration components that enable AI-powered functionality in production environments.
Create scalable data processing and application logic to support model inference, retrieval, search, and decision-support workflows.
Support the design and implementation of AI/ML solutions through software engineering, data engineering, and model integration practices.
Partner with data scientists, engineers, architects, and business stakeholders to define technical requirements and solution design.
Implement monitoring, logging, testing, and deployment practices to ensure reliability, performance, and maintainability of production systems.
Contribute to CI/CD pipelines, infrastructure-as-code practices, and secure software development standards.
Document architecture, technical designs, implementation details, and operational procedures.
Participate in code reviews, technical discussions, and knowledge-sharing activities to support team effectiveness and solution quality.
Requirements:
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field is required. Master's degree preferred.
Minimum of three (3) years of related experience in software engineering, data science, AI engineering, or machine learning engineering is required.
Demonstrated experience building and deploying production applications in cloud environments is required.
Experience developing backend services and integrating AWS-native services is required.
Prior experience supporting AI/ML solutions or intelligent automation initiatives is preferred.
Strong proficiency in Python and backend application development is required.
Strong hands-on experience with AWS-native services, including Lambda, DynamoDB, OpenSearch, Neptune, Bedrock, and SageMaker, is required.
Knowledge of AI engineering, machine learning deployment, and production support practices is required.
Experience with APIs, event-driven architecture, and distributed systems is required.
Understanding of cloud security, reliability, and performance best practices is preferred.
Experience with CI/CD pipelines, automated testing is required.
Ability to diagnose issues, optimize performance, and support production systems is required.
Strong written and verbal communication skills, including the ability to explain technical concepts to both technical and non-technical audiences, are required.
Ability to work independently, manage priorities, and deliver within established timelines is required.
Basic proficiency in Microsoft Word, Excel, and PowerPoint is required.