AWS AI Engineer

Senior AI and AWS engineer focused on delivering production-grade AI/ML capabilities on AWS, including retrieval-augmented generation, LLM fine-tuning, and cloud-native microservices in an enterprise setting.

Responsibilities

• Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3
• Design and implement AWS cloud services spanning infrastructure, machine learning, and AI platform tooling
• Develop LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks
• Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing
• Collaborate with internal stakeholders to translate business goals into secure, scalable AI systems
• Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform
• Support the development and evolution of reusable platform components for AI/ML operations
• Create and maintain technical documentation for the team and internal customers
• Exhibit excellent verbal and written communication skills in English

Requirements

• 7 years of hands-on software engineering experience with a strong focus on Python
• Experience with AWS services, especially Bedrock or SageMaker
• Familiarity with fine-tuning large language models or building datasets and deploying ML models to production
• Demonstrated experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Solid experience implementing RAG architectures and LangChain
• Experience in Infrastructure as Code best practices and building Terraform modules for AWS
• Strong background in Git-based version control, code reviews, and DevOps workflows
• Proven success delivering production-ready software with release pipeline integration

Technologies

• Python
• Bedrock
• SageMaker
• ECS
• Lambda
• Step Functions
• DynamoDB
• S3
• LangChain
• Transformers
• PyTorch
• TensorFlow
• Terraform
• Terraform Sentinel
• GitHub
• Hugging Face
• Node.js
• Golang
• AWS Config
• SCP
• AWS Organizations

Benefits

• Competitive base salary
• Medical, dental, and vision insurance coverage
• Optional life and disability insurance provided
• 401(k) with company match and optional profit sharing
• Paid vacation time
• Paid Bench time
• Training allowance offering
• Referral bonuses

Top Skills

• AWS services including Bedrock, SageMaker, ECS, and Lambda
• Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Proficiency in RAG architectures and ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Infrastructure as Code practices and Terraform module development for AWS
• Fine-tuning LLMs, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows
• AWS or relevant cloud certifications
• Data privacy and compliance best practices (PII handling, secure model deployment)
• Data science background or experience with structured and unstructured data
• Exposure to FinOps and cloud cost optimization
• Hugging Face, Node.js
• Policy as Code development (Terraform Sentinel)

What you'll do

• Design, build, and operate AI/ML applications in the cloud with real infrastructure, data, and users
• Develop retrieval-augmented generation systems and fine-tuned LLMs for production use
• Create cloud-native microservices and serverless components to support automation and real-time processing
• Collaborate with stakeholders to convert business needs into secure, scalable AI solutions
• Own the release lifecycle, CI/CD pipelines, GitHub SDLC, and infrastructure as code with Terraform
• Contribute to reusable platform components for AI/ML operations
• Maintain technical documentation for internal teams and customers