AWS AI Engineer

Responsibilities

• Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
• Implement AWS cloud services covering infrastructure, machine learning, and AI platform services.
• Develop LLM based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other 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 SDLC, and infrastructure as code with Terraform.
• Support development and evolution of reusable platform components for AI and ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Communicate effectively in English, both verbally and in writing.

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 cloud.
• 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
• Git, GitHub, Hugging Face
• Node.js, Golang

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

• 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 tools like Transformers, PyTorch, TensorFlow, and LangChain
  • Infrastructure as Code practices and building Terraform modules 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
  • Policy as Code development (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 (PII handling, secure model deployment)

Supervisory Responsibilities

• None

Minimum Knowledge, Skills, and Abilities Required

• 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.
• Demonstrated experience in Infrastructure as Code best practices and building Terraform modules for AWS cloud.
• Strong background in Git-based version control, code reviews, and DevOps workflows.
• Demonstrated 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 (PII handling, secure model deployment).

What You'll Get

• 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
• You will be eligible to earn referral bonuses