AWS AI Engineer

The Senior AWS AI Engineer will design and operate production AI/ML applications on AWS, with a focus on retrieval-augmented generation, fine-tuning large language models, and building cloud-native microservices.

Responsibilities

• Engage hands-on with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to implement AI solutions.
• Lead the development and deployment of AWS cloud services encompassing infrastructure, machine learning, and AI platform capabilities.
• Build and scale LLM driven applications, including Retrieval-Augmented Generation workflows using LangChain and related frameworks.
• Develop cloud-native microservices, APIs, and serverless components that enable intelligent automation and real-time data processing.
• Collaborate with internal stakeholders to translate business objectives 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 evolution of reusable platform components for AI/ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Demonstrate strong verbal and written communication in English.

Requirements

• Seven or more years of hands-on software engineering experience with a strong emphasis on Python.
• Proficiency with AWS services, particularly Bedrock or SageMaker.
• Experience fine-tuning large language models or building datasets and deploying ML models to production.
• Experience with AWS Organizations and policy guardrails such as SCPs and AWS Config.
• Solid background in implementing Retrieval-Augmented Generation architectures and LangChain.
• Experience following Infrastructure as Code best practices and building Terraform modules for AWS.
• Strong track record of Git-based version control, code reviews, and DevOps workflows.
• Proof of delivering production-ready software with integrated release pipelines.

Technologies

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

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

Top Skills

• Experience with AWS services including Bedrock, SageMaker, ECS, and Lambda
• Knowledge of AWS Organizations and policy guardrails (SCP, AWS Config)
• Proficiency in designing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Infrastructures as Code practices and Terraform module development for AWS
• 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, including secure model deployment and PII handling
• Background in data science or experience with structured and unstructured data
• Exposure to FinOps and cloud cost optimization
• Hugging Face, Node.js experience
• Policy as Code development, such as Terraform Sentinel