AWS AI Engineer

Based in Morton Grove, IL with remote options, this role offers a competitive base salary and a robust benefits package, including medical, dental, and vision coverage, a 401(k) with company match plus potential profit sharing, paid vacation, a training allowance, and referral bonuses. The position centers on building AI and ML applications on AWS, with emphasis on retrieval-augmented generation, fine-tuning large language models, and developing AWS-native microservices for enterprise automation.

Responsibilities

• Engage hands-on with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
• Implement AWS cloud solutions spanning infrastructure, machine learning workloads, and AI platform services.
• Work with LLM based applications, implementing 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, managing CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
• Support the development and evolution of reusable platform components for AI and ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Demonstrate strong verbal and written communication in English.

Requirements

• Proficiency with AWS Bedrock, SageMaker, ECS, and Lambda.
• Experience with AWS Organizations and policy guardrails such as SCPs and AWS Config.
• Background in implementing RAG architectures and working with ML tooling including Transformers, PyTorch, TensorFlow, and LangChain.
• Solid experience with Infrastructure as Code best practices and building Terraform modules for AWS cloud.
• Skill in fine-tuning large language models, building datasets, and deploying ML models to production.
• Git-based version control, code reviews, and DevOps workflows.

Technologies

• AWS Bedrock
• AWS SageMaker
• AWS ECS
• AWS Lambda
• AWS Step Functions
• DynamoDB
• S3
• LangChain
• Transformers
• PyTorch
• TensorFlow
• Terraform
• Terraform Sentinel
• Hugging Face
• Node.js
• Git

Benefits

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

Top Skills

Must Have

• AWS services Bedrock, SageMaker, ECS and Lambda
• Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Experience implementing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Infrastructure as Code best practices and building Terraform modules for AWS cloud
• Fine-tuning large language models, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows

Nice To Have

• AWS or relevant cloud certifications
• Data privacy and compliance practices (e.g., 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 (i.e., Terraform Sentinel)