AWS AI Engineer

The AWS AI Engineer role is a senior position focused on designing and delivering production-grade AI and ML capabilities on AWS. The emphasis is on retrieval-augmented generation, fine-tuning large language models, and building AWS-native microservices to support enterprise automation and governance.

Responsibilities

• Hands-on development with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
• Architect and implement AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
• Build and deploy LLM-based applications, including Retrieval-Augmented Generation using LangChain and other frameworks.
• Develop cloud-native microservices, APIs, and serverless components 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.
• Contribute to reusable platform components for AI/ML operations and tooling.
• Create and maintain technical documentation for teams and internal customers.
• Maintain strong written and verbal communication in English.

Requirements

• Minimum of seven years of hands-on software engineering experience with a strong emphasis on Python.
• Proficiency with AWS services, particularly Bedrock, SageMaker, ECS, and Lambda.
• Experience with AWS Organizations and policy guardrails, including SCP and AWS Config.
• Background in Retrieval-Augmented Generation architectures and using LangChain and other frameworks.
• Experience fine-tuning large language models, building datasets, and deploying ML models to production.
• Demonstrated IaC expertise, including building Terraform modules for AWS.
• Solid Git-based version control practices, code reviews, and DevOps workflows.
• Track record of delivering production-ready software with integrated release pipelines.

Technologies

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

Benefits

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

Supervisory Responsibilities

None

Minimum Knowledge, Skills, and Abilities Required

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

Nice-to-Haves

• AWS or relevant cloud certifications.
• Policy as Code development, e.g., Terraform Sentinel.
• Experience with Hugging Face, Golang, or Node.js.
• Exposure to FinOps and cloud cost optimization.
• Data science background or experience with structured/unstructured data.
• Awareness of data privacy and compliance best practices, including PII handling and secure model deployment.

What You’ll Get

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