AWS AI Engineer

Hudson Manpower is seeking a Senior AWS AI Engineer to architect and operate production AI/ML applications on AWS, with a focus on retrieval-augmented generation, fine-tuning large language models, and cloud-native microservices. The role centers on delivering secure AI services that integrate with live infrastructure data, built to scale and operate within live environments. The position is based in Pittsburgh, PA with remote work options and requires seven years of hands-on software engineering experience.

Responsibilities

• Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to implement cloud infrastructure, machine learning features, and AI platform capabilities.
• Own the deployment of AWS cloud services, spanning infrastructure, ML workflows, and AI platform services.
• Develop and maintain LLM based applications, including 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.
• Manage the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
• Support a reusable set of platform components for AI/ML operations and their evolution.
• Create and maintain technical documentation for the team and internal customers.
• Provide clear verbal and written communication in English.

Requirements

• Seven years of hands-on software engineering experience with a strong emphasis on Python.
• Experience with AWS services, particularly Bedrock or SageMaker.
• Familiarity with fine-tuning large language models or building datasets and deploying ML models to production.
• Experience navigating AWS organizations and policy guardrails such as SCP and AWS Config.
• Solid track record implementing RAG architectures and using LangChain.
• Proven experience with Infrastructure as Code best practices and building Terraform modules for AWS.
• 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, Git, GitHub
• Hugging Face, Node.js, Golang
• Terraform Sentinel, AWS Config, SCP

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
• Strong knowledge of AWS organizations and policy guardrails (SCP, AWS Config)
• Proficiency in 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
• Fine-tuning large language models, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows
• AWS or relevant cloud certifications
• Data privacy and compliance best practices, including 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 (Terraform Sentinel)