AWS AI Engineer

Hudson Manpower offers a competitive base salary, comprehensive medical, dental, and vision coverage, optional life and disability insurance, a 401(k) with company matching and potential profit sharing, paid vacation, a dedicated bench period, a training allowance, and referral bonuses. This role is based in Temple, TX with remote work options and focuses on building production-grade retrieval-augmented generation systems and cloud-native AI services on AWS.

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

Responsibilities

• Execute hands-on development with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and deploy AI capabilities.
• Lead the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform services.
• Work with LLM based applications and Retrieval-Augmented Generation using LangChain and related frameworks.
• Design 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-based SDLC, and infrastructure as code with Terraform.
• Support the 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.
• Experience with AWS organizations and policy guardrails (SCP, AWS Config).
• Solid background in implementing Retrieval-Augmented Generation and using LangChain.
• Experience with Infrastructure as Code best practices and building Terraform modules for AWS cloud.
• Strong track record with Git-based version control, code reviews, and DevOps workflows.
• Proven success delivering production-ready software with release pipeline integration.

Technologies

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

Top Skills

• Must Have AWS services including Bedrock, SageMaker, ECS and Lambda; experience with AWS organizations and policy guardrails (SCP, AWS Config); proficiency in implementing RAG architectures using frameworks and ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain; strong IaC practices and 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; proven ability to deliver production-ready software with release pipeline integration.
• Nice To Have AWS certifications or relevant cloud credentials; data privacy and compliance practices (PII handling, secure model deployment); data science background or experience with structured and unstructured data; exposure to FinOps and cloud cost optimization; experience with Hugging Face and Node.js; policy as code development such as Terraform Sentinel.