AWS AI Engineer

Senior AWS AI Engineer responsible for delivering AI/ML applications on AWS, focusing on retrieval-augmented generation (RAG), fine-tuning LLMs, and AWS-native microservices for enterprise automation.

Responsibilities

• Hands-on work with AWS services such as AWS Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate AI/ML capabilities.
• Design and implement AWS cloud services spanning infrastructure, ML platforms, and AI services to support enterprise automation.
• Develop LLM based applications, including Retrieval-Augmented Generation using LangChain and other frameworks.
• Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
• Collaborate with 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 development and evolution of reusable platform components for AI/ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Demonstrate excellent verbal and written communication skills in English.

Requirements

• Hands-on experience with AWS services such as Bedrock, SageMaker, ECS, and Lambda.
• Experience with AWS Organizations and policy guardrails, including SCPs and AWS Config.
• Proven experience implementing RAG architectures and working with ML frameworks/tools such as Transformers, PyTorch, TensorFlow, and LangChain.
• Strong Infrastructure as Code practices and experience building Terraform modules for AWS.
• Fine-tuning large language models, building datasets, and deploying ML models to production.
• Experience with Git-based version control, code reviews, and DevOps workflows.
• Minimum 7 years of relevant professional experience.

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 Bedrock
  • AWS SageMaker
  • AWS ECS
  • AWS Lambda
  • Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
  • Experience implementing RAG architectures and using ML tooling like Transformers, PyTorch, TensorFlow, and LangChain
  • Infrastructure as Code best practices and building Terraform modules for AWS
  • Fine-tuning LLMs, 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 best practices (PII handling, secure model deployment)
  • Data science background or experience with structured/unstructured data
  • Exposure to FinOps and cloud cost optimization
  • Hugging Face, Node.js
  • Policy as Code development (Terraform Sentinel)