Generative AI Engineer
TechStarsGroup
Atlanta, GA · Posted October 20, 2026
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How AI is used in this kind of work
Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Generative AI Engineer
About Our Client
Our client is an innovative healthcare technology company that's on a mission to revolutionize health insurance in the United States. They're building a more personalized, affordable, and transparent alternative to traditional health insurance models. Their diverse team brings together expertise from technology, healthcare policy, and various other backgrounds, all united by the goal of transforming a complex industry.
About the Role
We're recruiting a Generative AI Engineer with deep expertise in AWS and serverless architecture to optimize and refine large language model (LLM) interactions while ensuring seamless integration into cloud-based environments. This role requires experience in designing and deploying scalable, serverless AI applications using Amazon Bedrock, AWS Step Functions, AWS Lambda, API Gateway, DynamoDB, and other cloud-native services.
What You'll Do
Develop, optimize, and refine AI-generated outputs through advanced prompt engineering techniques
Design agentic systems leveraging AWS Step Functions and Amazon Bedrock
Design and implement serverless workflows to support AI-driven applications using AWS Lambda, API Gateway, and DynamoDB
Build and maintain scalable prompt automation pipelines using AWS services
Explore prompt strategies to enhance AI model responses and mitigate inconsistencies or hallucinations
Conduct performance monitoring, logging, and error handling for AI-related API calls and workflows in AWS
Stay updated on advancements in AI, LLMs, and cloud computing, applying new techniques to improve model performance
Develop documentation, best practices, and internal tooling for prompt engineering within a serverless ecosystem
What You'll Bring
Bachelor's or Master's degree in Computer Science, Information Systems, Business Administration, or a related field
4+ years of professional experience in software engineering, with a focus on AI or machine learning platforms
Fluency in AWS serverless architecture, including Lambda, API Gateway, Step Functions, S3, DynamoDB, and IAM
Strong TypeScript programming skills
Hands-on experience with AI APIs such as OpenAI, Anthropic, and Hugging Face
Understanding of LLM behavior and prompt engineering techniques, including model biases, tokenization, embeddings, and response optimization
Cloud-native development expertise, including deploying and scaling AI applications in AWS
Experience with infrastructure as code (IaC) using AWS SAM, AWS CDK, Serverless framework, or CloudFormation
Familiarity with monitoring and logging tools such as AWS CloudWatch, X-Ray, or Datadog
Ability to troubleshoot performance bottlenecks in serverless environments and optimize for cost-efficiency
What You'll Get
Competitive salary, bonus opportunity, and equity package
Comprehensive Medical, Dental, and Vision benefits
A 401k retirement plan
Paid vacation and company holidays
Opportunity to make an impact at a rapidly growing mission-driven company transforming healthcare in the U.S.